Remote MLOps Engineer Jobs

MLOps Engineer Python Machine Learning GCP Kubernetes CI/CD Remote UK About Us We are an early-stage biotechnology company using live cell imaging and artificial intelligence to predict stem cell behavior. Our goal is to improve the manufacturing of human cells for research and therapeutic use by enabling a deeper understanding of cell differentiation. Founded in 2022 as a spin-out from a leading UK research institution we are backed by prominent venture capital firms with experience investing in AI life sciences and deep tech startups. What We’re Building At the core of our technology is a proprietary AI-powered SaaS platform that enables scientists to visualize track and predict cell differentiation in real-time. Designed to support high-throughput experiments the platform integrates microscopy computer vision cloud infrastructure and machine learning to accelerate advancements in cell biology and biomanufacturing. We are currently seeking a DevOps / MLOps Engineer to help scale our cloud infrastructure and machine learning workflows as part of our growing technical team. Key Responsibilities Develop and maintain infrastructure for our SaaS platform that delivers AI-driven computer vision tools to researchers and scientists. Collaborate with a multidisciplinary team of machine learning engineers data scientists software developers and biologists. Build and support GPU-accelerated environments for training and real-time inference of deep learning models. Deploy and manage ML pipelines using tools like Docker Kubernetes and frameworks such as Kubeflow or Ray. Create and document APIs that enable internal and external users to access data and model outputs. Implement secure authentication and authorization systems for platform users. Maintain and improve our cloud platform’s reliability security and compliance (e.g. GDPR HIPAA readiness). Automate testing training and deployment of models through robust CI/CD pipelines. Monitor and troubleshoot performance issues across data and inference workflows in production. What We’re Looking For 5+ years of experience in DevOps MLOps SRE or Data Engineering roles. Strong proficiency with public cloud platforms (e.g. GCP AWS or Azure) with preference for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes including cluster and node management. Familiarity with ML workload orchestration using Docker Kubeflow Ray or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale datasets and optimizing data pipelines. Strong communication skills and the ability to clearly document complex systems. A self-driven mindset and interest in staying current with trends in cloud data and ML tools. Experience leading infrastructure efforts in greenfield or early-stage environments. Nice to Have Experience working on SaaS platforms in biotech healthcare or life sciences. Experience with real-time ML inference and production monitoring. Familiarity with computer vision models and workflows. Understanding of data privacy regulations and scientific data formats (e.g. TIFF OME-TIFF). Background working in early-stage startups (seed or Series A). What We Offer Competitive salary and benefits. Growth opportunities and professional development. A collaborative forward-thinking environment at the intersection of AI and biotechnology. A meaningful mission with the potential to impact healthcare through innovation in science and technology. Why Join Us You'll be part of a rapidly growing interdisciplinary team working on complex challenges in AI and biology. Your contributions will shape the technical foundation of our product and accelerate both scientific discovery and therapeutic development. This is an opportunity to make a tangible impact during a pivotal stage of growth. MLOps Engineer Python Machine Learning GCP Kubernetes CI/CD Remote UK

"Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs but promotes jobs on LinkedIn on behalf of its direct clients recruitment ad agencies and marketing partners. Lensa partners with DirectEmployers to promote this job for CDM Smith. Clicking ""Apply Now"" or ""Read more"" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice. 42502BR Requisition ID 42502BR Business Unit TRX Job Description Trinnex a wholly owned subsidiary of CDM Smith is seeking a MLOps Engineer with specialization in AI platform to join our growing team. Trinnex is building next generation tools that integrate sensor/IoT data models geospatial data and machine learning to solve unique engineering and environmental issues. This position is based in Toronto Ontario candidates located in Vancouver BC or Edmonton Alberta may also be considered. In this role you will own the operational backbone for our AI and Data Engineering products. You will be responsible for the end-to-end production lifecycle of our ML models from helping build the application services that wrap them to creating the automated systems for their deployment. Your ultimate goal is to ensure the overall health scalability and reliability of these machine learning systems in production. This requires close collaboration with internal resources to research and implement MLOps best practices driving continuous improvement and automation across our platforms. Responsibilities Design build and maintain scalable and reliable infrastructure to support the entire machine learning lifecycle from experimentation and training to deployment and monitoring. Develop and manage robust CI/CD pipelines for ML models and associated software services ensuring automated high-quality releases. Collaborate closely with Data Scientists to containerize deploy and operationalize machine learning models implementing solutions for both batch prediction and real-time inference use cases. Collaborate with teams to architect generative AI applications providing expert guidance on connecting LLMs to proprietary data sources and enabling them to execute tasks on behalf of users. Champion MLOps best practices and empowers the Data Science team by providing guidance training and support for new tools and automated workflows. Partner with Software Engineers to define and implement modern service architectures including microservices and APIs for ML-powered applications. Implement and manage cloud infrastructure using Infrastructure as Code (IaC) principles to ensure environments are reproducible secure and auditable. Establish and maintain comprehensive monitoring logging and alerting systems to track model performance data drift and infrastructure health and aid in incident response. Work with cybersecurity and architecture teams to design and enforce security best practices across our cloud environment including network configuration identity management and data protection. Maintain clear and detailed documentation for MLOps processes infrastructure and best practices. Skills And Abilities Excellent software engineering fundamentals with a solid understanding of modern software service architecture (e.g. microservices APIs) and CI/CD principles. Deep hands-on expertise with containerization (Docker) and container orchestration (Kubernetes). Proven experience designing building and securing infrastructure on a major cloud platform (e.g. GCP AWS Azure) with a firm grasp of core concepts like identity and access management (IAM) and secure network architecture including VPCs firewall policies and segmentation. Demonstrable understanding of the end-to-end machine learning lifecycle and experience deploying models for both batch and real-time/live inference workloads. Experience working with and understanding the trade-offs between different data storage paradigms such as relational databases (e.g. PostgreSQL) analytical data warehouses (e.g. BigQuery) and cloud object storage (e.g. GCS S3). Solid understanding of Python. Excellent communication interpersonal and organizational skills with a demonstrated ability to manage and prioritize multiple tasks effectively both independently and as part of a team. Job Title MLOps Engineer (Remote) Group TXUP Employment Type Regular Minimum Qualifications Bachelor's Degree. 5 years of related experience. Equivalent additional directly related experience will be considered in lieu of a degree. Domestic and/or international travel may be required. The frequency of travel is contingent on specific duties responsibilities and the essential functions of the position which may vary depending on workload and project demands. Preferred Qualifications Professional experience with Google Cloud Platform (GCP) especially its AI/ML services like Vertex AI. Hands-on experience building applications that connect LLMs to external systems such as using Retrieval-Augmented Generation (RAG) for querying data or enabling tool use (function calling). Familiarity with frameworks like LangChain is a plus. Experience with core MLOps components including experiment tracking (e.g. MLFlow Vertex AI Experiments) and model registries. Experience with modern workflow orchestration frameworks designed for machine learning (e.g. Kubeflow Pipelines Flyte or Prefect). Intermediate to advanced knowledge of Infrastructure as Code (IaC) tools particularly Terraform. Experience managing Kubernetes applications using Helm. Experience with specific CI/CD tools (e.g. Azure DevOps Pipelines). Hands-on experience with service mesh technologies like Istio. Broader coding and debugging skills in languages such as Javascript C# Java or Go. Job Site Location: Canada - Toronto Agency Disclaimer All vendors must have a signed CDM Smith Placement Agreement from the CDM Smith Recruitment Center Manager to receive payment for your placement. Verbal or written commitments from any other member of the CDM Smith staff will not be considered binding terms. All unsolicited resumes sent to CDM Smith and any resume submitted to any employee outside of CDM Smith Recruiting Center Team (RCT) will be considered property of CDM Smith. CDM Smith will not be held liable to pay a placement fee. Amount Of Travel Required 0% Assignment Category Fulltime-Regular Background Check And Drug Testing Information CDM Smith Inc. and its divisions and subsidiaries (hereafter collectively referred to as “CDM Smith”) reserves the right to require background checks including criminal employment education licensure etc. as well as credit and motor vehicle when applicable for certain positions. In addition CDM Smith may conduct drug testing for designated positions. Background checks are conducted after an offer of employment has been made in the United States. The timing of when background checks will be conducted on candidates for positions outside the United States will vary based on country statutory law but in no case will the background check precede an interview. CDM Smith will conduct interviews of qualified individuals prior to requesting a criminal background check and no job application submitted prior to such interview shall inquire into an applicant's criminal history. If this position is subject to a background check for any convictions related to its responsibilities and requirements employment will be contingent upon successful completion of a background investigation including criminal history. Criminal history will not automatically disqualify a candidate. In addition during employment individuals may be required by CDM Smith or a CDM Smith client to successfully complete additional background checks including motor vehicle record as well as drug testing. Why Trinnex?: If you are passionate about water and technology Trinnex is the place for you! Trinnex is a visionary company that is transforming the way water resources are managed and protected. By combining cutting-edge digital technologies such as sensor/IoT data models geospatial data and AI/machine learning we create innovative smart and scalable solutions that make a difference. Whether it's optimizing water supply and demand detecting leaks and anomalies or enhancing water quality and resilience Trinnex delivers value and impact to public sector clients across the country. Visa Sponsorship Available No - Please note that all applicants must be legally eligible to work in Canada for the Company at the time of hire. Furthermore this is not a position for which the Company is offering immigration application sponsorship or support. Pay Range Minimum $144477 Pay Range Maximum $252824 Accessibility To make an accessibility request please click here (https://cdn.prod.website-files.com/61548ab101cefac517e6d387/66c8cfca63ab816f9fc637c2WebsiteAccesibilityRequestforApplicationstoCanadianPositions.pdf) If you have questions about this posting please contact support@lensa.com"

"Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs but promotes jobs on LinkedIn on behalf of its direct clients recruitment ad agencies and marketing partners. Lensa partners with DirectEmployers to promote this job for CDM Smith. Clicking ""Apply Now"" or ""Read more"" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice. 42502BR Requisition ID 42502BR Business Unit TRX Job Description Trinnex a wholly owned subsidiary of CDM Smith is seeking a MLOps Engineer with specialization in AI platform to join our growing team. Trinnex is building next generation tools that integrate sensor/IoT data models geospatial data and machine learning to solve unique engineering and environmental issues. This position is based in Toronto Ontario candidates located in Vancouver BC or Edmonton Alberta may also be considered. In this role you will own the operational backbone for our AI and Data Engineering products. You will be responsible for the end-to-end production lifecycle of our ML models from helping build the application services that wrap them to creating the automated systems for their deployment. Your ultimate goal is to ensure the overall health scalability and reliability of these machine learning systems in production. This requires close collaboration with internal resources to research and implement MLOps best practices driving continuous improvement and automation across our platforms. Responsibilities Design build and maintain scalable and reliable infrastructure to support the entire machine learning lifecycle from experimentation and training to deployment and monitoring. Develop and manage robust CI/CD pipelines for ML models and associated software services ensuring automated high-quality releases. Collaborate closely with Data Scientists to containerize deploy and operationalize machine learning models implementing solutions for both batch prediction and real-time inference use cases. Collaborate with teams to architect generative AI applications providing expert guidance on connecting LLMs to proprietary data sources and enabling them to execute tasks on behalf of users. Champion MLOps best practices and empowers the Data Science team by providing guidance training and support for new tools and automated workflows. Partner with Software Engineers to define and implement modern service architectures including microservices and APIs for ML-powered applications. Implement and manage cloud infrastructure using Infrastructure as Code (IaC) principles to ensure environments are reproducible secure and auditable. Establish and maintain comprehensive monitoring logging and alerting systems to track model performance data drift and infrastructure health and aid in incident response. Work with cybersecurity and architecture teams to design and enforce security best practices across our cloud environment including network configuration identity management and data protection. Maintain clear and detailed documentation for MLOps processes infrastructure and best practices. Skills And Abilities Excellent software engineering fundamentals with a solid understanding of modern software service architecture (e.g. microservices APIs) and CI/CD principles. Deep hands-on expertise with containerization (Docker) and container orchestration (Kubernetes). Proven experience designing building and securing infrastructure on a major cloud platform (e.g. GCP AWS Azure) with a firm grasp of core concepts like identity and access management (IAM) and secure network architecture including VPCs firewall policies and segmentation. Demonstrable understanding of the end-to-end machine learning lifecycle and experience deploying models for both batch and real-time/live inference workloads. Experience working with and understanding the trade-offs between different data storage paradigms such as relational databases (e.g. PostgreSQL) analytical data warehouses (e.g. BigQuery) and cloud object storage (e.g. GCS S3). Solid understanding of Python. Excellent communication interpersonal and organizational skills with a demonstrated ability to manage and prioritize multiple tasks effectively both independently and as part of a team. Job Title MLOps Engineer (Remote) Group TXUP Employment Type Regular Minimum Qualifications Bachelor's Degree. 5 years of related experience. Equivalent additional directly related experience will be considered in lieu of a degree. Domestic and/or international travel may be required. The frequency of travel is contingent on specific duties responsibilities and the essential functions of the position which may vary depending on workload and project demands. Preferred Qualifications Professional experience with Google Cloud Platform (GCP) especially its AI/ML services like Vertex AI. Hands-on experience building applications that connect LLMs to external systems such as using Retrieval-Augmented Generation (RAG) for querying data or enabling tool use (function calling). Familiarity with frameworks like LangChain is a plus. Experience with core MLOps components including experiment tracking (e.g. MLFlow Vertex AI Experiments) and model registries. Experience with modern workflow orchestration frameworks designed for machine learning (e.g. Kubeflow Pipelines Flyte or Prefect). Intermediate to advanced knowledge of Infrastructure as Code (IaC) tools particularly Terraform. Experience managing Kubernetes applications using Helm. Experience with specific CI/CD tools (e.g. Azure DevOps Pipelines). Hands-on experience with service mesh technologies like Istio. Broader coding and debugging skills in languages such as Javascript C# Java or Go. Job Site Location: Canada - Toronto Agency Disclaimer All vendors must have a signed CDM Smith Placement Agreement from the CDM Smith Recruitment Center Manager to receive payment for your placement. Verbal or written commitments from any other member of the CDM Smith staff will not be considered binding terms. All unsolicited resumes sent to CDM Smith and any resume submitted to any employee outside of CDM Smith Recruiting Center Team (RCT) will be considered property of CDM Smith. CDM Smith will not be held liable to pay a placement fee. Amount Of Travel Required 0% Assignment Category Fulltime-Regular Background Check And Drug Testing Information CDM Smith Inc. and its divisions and subsidiaries (hereafter collectively referred to as “CDM Smith”) reserves the right to require background checks including criminal employment education licensure etc. as well as credit and motor vehicle when applicable for certain positions. In addition CDM Smith may conduct drug testing for designated positions. Background checks are conducted after an offer of employment has been made in the United States. The timing of when background checks will be conducted on candidates for positions outside the United States will vary based on country statutory law but in no case will the background check precede an interview. CDM Smith will conduct interviews of qualified individuals prior to requesting a criminal background check and no job application submitted prior to such interview shall inquire into an applicant's criminal history. If this position is subject to a background check for any convictions related to its responsibilities and requirements employment will be contingent upon successful completion of a background investigation including criminal history. Criminal history will not automatically disqualify a candidate. In addition during employment individuals may be required by CDM Smith or a CDM Smith client to successfully complete additional background checks including motor vehicle record as well as drug testing. Why Trinnex?: If you are passionate about water and technology Trinnex is the place for you! Trinnex is a visionary company that is transforming the way water resources are managed and protected. By combining cutting-edge digital technologies such as sensor/IoT data models geospatial data and AI/machine learning we create innovative smart and scalable solutions that make a difference. Whether it's optimizing water supply and demand detecting leaks and anomalies or enhancing water quality and resilience Trinnex delivers value and impact to public sector clients across the country. Visa Sponsorship Available No - Please note that all applicants must be legally eligible to work in Canada for the Company at the time of hire. Furthermore this is not a position for which the Company is offering immigration application sponsorship or support. Pay Range Minimum $144477 Pay Range Maximum $252824 Accessibility To make an accessibility request please click here (https://cdn.prod.website-files.com/61548ab101cefac517e6d387/66c8cfca63ab816f9fc637c2WebsiteAccesibilityRequestforApplicationstoCanadianPositions.pdf) If you have questions about this posting please contact support@lensa.com"

"Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs but promotes jobs on LinkedIn on behalf of its direct clients recruitment ad agencies and marketing partners. Lensa partners with DirectEmployers to promote this job for CDM Smith. Clicking ""Apply Now"" or ""Read more"" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice. 42502BR Requisition ID 42502BR Business Unit TRX Job Description Trinnex a wholly owned subsidiary of CDM Smith is seeking a MLOps Engineer with specialization in AI platform to join our growing team. Trinnex is building next generation tools that integrate sensor/IoT data models geospatial data and machine learning to solve unique engineering and environmental issues. This position is based in Toronto Ontario candidates located in Vancouver BC or Edmonton Alberta may also be considered. In this role you will own the operational backbone for our AI and Data Engineering products. You will be responsible for the end-to-end production lifecycle of our ML models from helping build the application services that wrap them to creating the automated systems for their deployment. Your ultimate goal is to ensure the overall health scalability and reliability of these machine learning systems in production. This requires close collaboration with internal resources to research and implement MLOps best practices driving continuous improvement and automation across our platforms. Responsibilities Design build and maintain scalable and reliable infrastructure to support the entire machine learning lifecycle from experimentation and training to deployment and monitoring. Develop and manage robust CI/CD pipelines for ML models and associated software services ensuring automated high-quality releases. Collaborate closely with Data Scientists to containerize deploy and operationalize machine learning models implementing solutions for both batch prediction and real-time inference use cases. Collaborate with teams to architect generative AI applications providing expert guidance on connecting LLMs to proprietary data sources and enabling them to execute tasks on behalf of users. Champion MLOps best practices and empowers the Data Science team by providing guidance training and support for new tools and automated workflows. Partner with Software Engineers to define and implement modern service architectures including microservices and APIs for ML-powered applications. Implement and manage cloud infrastructure using Infrastructure as Code (IaC) principles to ensure environments are reproducible secure and auditable. Establish and maintain comprehensive monitoring logging and alerting systems to track model performance data drift and infrastructure health and aid in incident response. Work with cybersecurity and architecture teams to design and enforce security best practices across our cloud environment including network configuration identity management and data protection. Maintain clear and detailed documentation for MLOps processes infrastructure and best practices. Skills And Abilities Excellent software engineering fundamentals with a solid understanding of modern software service architecture (e.g. microservices APIs) and CI/CD principles. Deep hands-on expertise with containerization (Docker) and container orchestration (Kubernetes). Proven experience designing building and securing infrastructure on a major cloud platform (e.g. GCP AWS Azure) with a firm grasp of core concepts like identity and access management (IAM) and secure network architecture including VPCs firewall policies and segmentation. Demonstrable understanding of the end-to-end machine learning lifecycle and experience deploying models for both batch and real-time/live inference workloads. Experience working with and understanding the trade-offs between different data storage paradigms such as relational databases (e.g. PostgreSQL) analytical data warehouses (e.g. BigQuery) and cloud object storage (e.g. GCS S3). Solid understanding of Python. Excellent communication interpersonal and organizational skills with a demonstrated ability to manage and prioritize multiple tasks effectively both independently and as part of a team. Job Title MLOps Engineer (Remote) Group TXUP Employment Type Regular Minimum Qualifications Bachelor's Degree. 5 years of related experience. Equivalent additional directly related experience will be considered in lieu of a degree. Domestic and/or international travel may be required. The frequency of travel is contingent on specific duties responsibilities and the essential functions of the position which may vary depending on workload and project demands. Preferred Qualifications Professional experience with Google Cloud Platform (GCP) especially its AI/ML services like Vertex AI. Hands-on experience building applications that connect LLMs to external systems such as using Retrieval-Augmented Generation (RAG) for querying data or enabling tool use (function calling). Familiarity with frameworks like LangChain is a plus. Experience with core MLOps components including experiment tracking (e.g. MLFlow Vertex AI Experiments) and model registries. Experience with modern workflow orchestration frameworks designed for machine learning (e.g. Kubeflow Pipelines Flyte or Prefect). Intermediate to advanced knowledge of Infrastructure as Code (IaC) tools particularly Terraform. Experience managing Kubernetes applications using Helm. Experience with specific CI/CD tools (e.g. Azure DevOps Pipelines). Hands-on experience with service mesh technologies like Istio. Broader coding and debugging skills in languages such as Javascript C# Java or Go. Job Site Location: Canada - Toronto Agency Disclaimer All vendors must have a signed CDM Smith Placement Agreement from the CDM Smith Recruitment Center Manager to receive payment for your placement. Verbal or written commitments from any other member of the CDM Smith staff will not be considered binding terms. All unsolicited resumes sent to CDM Smith and any resume submitted to any employee outside of CDM Smith Recruiting Center Team (RCT) will be considered property of CDM Smith. CDM Smith will not be held liable to pay a placement fee. Amount Of Travel Required 0% Assignment Category Fulltime-Regular Background Check And Drug Testing Information CDM Smith Inc. and its divisions and subsidiaries (hereafter collectively referred to as “CDM Smith”) reserves the right to require background checks including criminal employment education licensure etc. as well as credit and motor vehicle when applicable for certain positions. In addition CDM Smith may conduct drug testing for designated positions. Background checks are conducted after an offer of employment has been made in the United States. The timing of when background checks will be conducted on candidates for positions outside the United States will vary based on country statutory law but in no case will the background check precede an interview. CDM Smith will conduct interviews of qualified individuals prior to requesting a criminal background check and no job application submitted prior to such interview shall inquire into an applicant's criminal history. If this position is subject to a background check for any convictions related to its responsibilities and requirements employment will be contingent upon successful completion of a background investigation including criminal history. Criminal history will not automatically disqualify a candidate. In addition during employment individuals may be required by CDM Smith or a CDM Smith client to successfully complete additional background checks including motor vehicle record as well as drug testing. Why Trinnex?: If you are passionate about water and technology Trinnex is the place for you! Trinnex is a visionary company that is transforming the way water resources are managed and protected. By combining cutting-edge digital technologies such as sensor/IoT data models geospatial data and AI/machine learning we create innovative smart and scalable solutions that make a difference. Whether it's optimizing water supply and demand detecting leaks and anomalies or enhancing water quality and resilience Trinnex delivers value and impact to public sector clients across the country. Visa Sponsorship Available No - Please note that all applicants must be legally eligible to work in Canada for the Company at the time of hire. Furthermore this is not a position for which the Company is offering immigration application sponsorship or support. Pay Range Minimum $144477 Pay Range Maximum $252824 Accessibility To make an accessibility request please click here (https://cdn.prod.website-files.com/61548ab101cefac517e6d387/66c8cfca63ab816f9fc637c2WebsiteAccesibilityRequestforApplicationstoCanadianPositions.pdf) If you have questions about this posting please contact support@lensa.com"

Trinnex a wholly owned subsidiary of CDM Smith is seeking a MLOps Engineer with specialization in AI platform to join our growing team. Trinnex is building next generation tools that integrate sensor/IoT data models geospatial data and machine learning to solve unique engineering and environmental issues. This position is based in Toronto Ontario candidates located in Vancouver BC or Edmonton Alberta may also be considered. In this role you will own the operational backbone for our AI and Data Engineering products. You will be responsible for the end-to-end production lifecycle of our ML models from helping build the application services that wrap them to creating the automated systems for their deployment. Your ultimate goal is to ensure the overall health scalability and reliability of these machine learning systems in production. This requires close collaboration with internal resources to research and implement MLOps best practices driving continuous improvement and automation across our platforms. Responsibilities: Design build and maintain scalable and reliable infrastructure to support the entire machine learning lifecycle from experimentation and training to deployment and monitoring. Develop and manage robust CI/CD pipelines for ML models and associated software services ensuring automated high-quality releases. Collaborate closely with Data Scientists to containerize deploy and operationalize machine learning models implementing solutions for both batch prediction and real-time inference use cases. Collaborate with teams to architect generative AI applications providing expert guidance on connecting LLMs to proprietary data sources and enabling them to execute tasks on behalf of users. Champion MLOps best practices and empowers the Data Science team by providing guidance training and support for new tools and automated workflows. Partner with Software Engineers to define and implement modern service architectures including microservices and APIs for ML-powered applications. Implement and manage cloud infrastructure using Infrastructure as Code (IaC) principles to ensure environments are reproducible secure and auditable. Establish and maintain comprehensive monitoring logging and alerting systems to track model performance data drift and infrastructure health and aid in incident response. Work with cybersecurity and architecture teams to design and enforce security best practices across our cloud environment including network configuration identity management and data protection. Maintain clear and detailed documentation for MLOps processes infrastructure and best practices. Skills and Abilities: Excellent software engineering fundamentals with a solid understanding of modern software service architecture (e.g. microservices APIs) and CI/CD principles. Deep hands-on expertise with containerization (Docker) and container orchestration (Kubernetes). Proven experience designing building and securing infrastructure on a major cloud platform (e.g. GCP AWS Azure) with a firm grasp of core concepts like identity and access management (IAM) and secure network architecture including VPCs firewall policies and segmentation. Demonstrable understanding of the end-to-end machine learning lifecycle and experience deploying models for both batch and real-time/live inference workloads. Experience working with and understanding the trade-offs between different data storage paradigms such as relational databases (e.g. PostgreSQL) analytical data warehouses (e.g. BigQuery) and cloud object storage (e.g. GCS S3). Solid understanding of Python. Excellent communication interpersonal and organizational skills with a demonstrated ability to manage and prioritize multiple tasks effectively both independently and as part of a team. #LI-LP1 #LI-REMOTE Minimum Qualifications Bachelor's Degree. 5 years of related experience. Equivalent additional directly related experience will be considered in lieu of a degree. Domestic and/or international travel may be required. The frequency of travel is contingent on specific duties responsibilities and the essential functions of the position which may vary depending on workload and project demands. Preferred Qualifications Professional experience with Google Cloud Platform (GCP) especially its AI/ML services like Vertex AI. Hands-on experience building applications that connect LLMs to external systems such as using Retrieval-Augmented Generation (RAG) for querying data or enabling tool use (function calling). Familiarity with frameworks like LangChain is a plus. Experience with core MLOps components including experiment tracking (e.g. MLFlow Vertex AI Experiments) and model registries. Experience with modern workflow orchestration frameworks designed for machine learning (e.g. Kubeflow Pipelines Flyte or Prefect). Intermediate to advanced knowledge of Infrastructure as Code (IaC) tools particularly Terraform. Experience managing Kubernetes applications using Helm. Experience with specific CI/CD tools (e.g. Azure DevOps Pipelines). Hands-on experience with service mesh technologies like Istio. Broader coding and debugging skills in languages such as Javascript C# Java or Go. Amount of Travel Required 0% Background Check and Drug Testing Information CDM Smith Inc. and its divisions and subsidiaries (hereafter collectively referred to as “CDM Smith”) reserves the right to require background checks including criminal employment education licensure etc. as well as credit and motor vehicle when applicable for certain positions. In addition CDM Smith may conduct drug testing for designated positions. Background checks are conducted after an offer of employment has been made in the United States. The timing of when background checks will be conducted on candidates for positions outside the United States will vary based on country statutory law but in no case will the background check precede an interview. CDM Smith will conduct interviews of qualified individuals prior to requesting a criminal background check and no job application submitted prior to such interview shall inquire into an applicant's criminal history. If this position is subject to a background check for any convictions related to its responsibilities and requirements employment will be contingent upon successful completion of a background investigation including criminal history. Criminal history will not automatically disqualify a candidate. In addition during employment individuals may be required by CDM Smith or a CDM Smith client to successfully complete additional background checks including motor vehicle record as well as drug testing. Agency Disclaimer All vendors must have a signed CDM Smith Placement Agreement from the CDM Smith Recruitment Center Manager to receive payment for your placement. Verbal or written commitments from any other member of the CDM Smith staff will not be considered binding terms. All unsolicited resumes sent to CDM Smith and any resume submitted to any employee outside of CDM Smith Recruiting Center Team (RCT) will be considered property of CDM Smith. CDM Smith will not be held liable to pay a placement fee. Pay Range Minimum $144477 Pay Range Maximum $252824 Business Unit TRX Group TXUP Assignment Category Fulltime-Regular Employment Type Regular Visa Sponsorship Available No - Please note that all applicants must be legally eligible to work in Canada for the Company at the time of hire. Furthermore this is not a position for which the Company is offering immigration application sponsorship or support. Accessibility To make an accessibility request please click here

UPMC Health Plan is seeking a skilled and motivated MLOps Engineer to join our AI Solutions team. In this role you will be responsible for designing building and maintaining the infrastructure and tools that enable the deployment monitoring and scaling of machine learning models in production. You will work closely with data scientists software engineers and Cloud Engineering teams to streamline the ML lifecycle and ensure robust secure and efficient model operations. Responsibilities: Develop and maintain CI/CD pipelines for machine learning workflows including model training validation deployment and monitoring. Collaborate with data scientists to productionize ML models and ensure reproducibility and scalability. Design and implement model versioning model registry and automated retraining strategies. Monitor model performance and data drift in production environments and implement alerting and rollback mechanisms. Optimize infrastructure for cost performance and reliability using cloud-native tools and services (e.g. AWS Azure GCP). Ensure compliance with data governance security and privacy standards throughout the ML lifecycle. Automate data ingestion feature engineering and model evaluation processes. Contribute to the development of internal tools and frameworks to support experimentation and deployment. Document best practices and provide guidance to cross-functional teams on MLOps principles. Masters degree in Computer Science Engineering or a related field or Bachelors in related fields with 5+ years relevant professional experience. 3+ years of experience in MLOps DevOps or ML Engineering roles. Preference will be given to those with MLOps experience. 3 years relevant work experience after completion of terminal degree is highly preferred. Experience deploying and building data science and machine learning solutions. Proficiency with ML lifecycle tools and orchestration frameworks. Hands on experience with cloud platforms (Azure preferred) Solid understanding of CI/CD principles. Familiarity with drift monitoring logging and alert frameworks. Licensure Certifications and Clearances: Act 34 UPMC is an Equal Opportunity Employer/Disability/Veteran

MLOps Engineer - 100% Remote (Spain) Salaries - €70 - 90k + package Location - Remote (must be in Spain) Must have a degree in Computer Science. Multiple headcount The client Our client specialises in facilitating cross-border payment solutions helping global businesses process transactions in emerging markets. They provide a seamless way for companies to accept local payment methods and make payouts without needing a local presence. What Makes a Great Candidate Proven experience implementing and deploying machine learning solutions. Advanced knowledge of Python SQL and Spark. Knowledge in some of the following tools or similar technologies: Docker Git Bash Scripting FastAPI Sagemaker Studio Airflow Cloudformation. Knowledge of data architectures and systems integration. Ability to solve complex software system issues. Experience with cloud platforms like AWS and GCP. Experience in payments or other financial systems is a plus. A degree in Computer Science or a related field ideally from a top global university. If you are a passionate engineer who enjoys solving challenging problems in a fast-paced environment then this could be a great fit. Join the team in Spain to make a difference today. Spain - 100% remote Salaries - €70 - 90k + package MLOps Engineer - ML / Python / Spark / Kubernetes / Flink If this is of interest please apply or reach out to will.semple@oliverbernard.com.

Job Posting - Salary Range: $133109 - $239596 Company Description Experian is a global data and technology company powering opportunities for people and businesses around the world. We help to redefine lending practices uncover and prevent fraud simplify healthcare create digital marketing solutions and gain deeper insights into the automotive market all using our unique combination of data analytics and software. We also assist millions of people to realise their financial goals and help them to save time and money. We operate across a range of markets from financial services to healthcare automotive agrifinance insurance and many more industry segments. We invest in people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN) we have a team of 23300 people across 32 countries. Our corporate headquarters are in Dublin Ireland. Learn more at experianplc.com. Job Description We are looking for an experienced MLOps Engineer to build and scale machine learning solutions that address critical challenges in the healthcare revenue cycle. You will report to Experian Health and focus on operationalizing ML models ensuring deployment pipelines and maintaining scalable secure and ML infrastructure on AWS collaborate with data scientists software engineers and product teams to bring ML products from prototype to production with a emphasis on automation monitoring and continuous improvement. You'll have opportunity to: + Develop scalable MLOps pipelines for model training validation deployment and monitoring using AWS services + Implement infrastructure as code and CI/CD workflows to support rapid experimentation and reliable production releases + Collaborate with data scientists to productionize ML models and ensure reproducibility versioning and traceability + Monitor model performance and data drift in production environments and implement automated retraining and alerting mechanisms + Improve ML workflows using tools such as SageMaker Airflow Docker Kubernetes (EKS) and Step Functions + Ensure compliance with healthcare data standards and security best practices (e.g. HIPAA) Qualifications Bachelor's degree in Computer Science Engineering Data Science or a related field 3+ years' experience in MLOps DevOps or ML engineering roles 3+ years' experience with AWS services for ML (e.g. SageMaker Lambda Step Functions S3 ECR CloudWatch) Proficiency with containerization and orchestration tools (Docker Kubernetes/EKS). 3+ years' experience with ML lifecycle tools such as MLflow TensorFlow Serving or Kubeflow and with CI/CD pipelines infrastructure as code (e.g. Terraform CloudFormation) and monitoring/logging tools Experience in the healthcare domain especially with claims or EHR data and familiarity with standards like ICD and CPT Exposure to NLP Bayesian modeling or real-time ML systems Familiarity with Agile development methodologies AWS certifications (e.g. Machine Learning Specialty DevOps Engineer) Benefits/Perks Additional Information Great compensation package and bonus plan Core benefits including medical dental vision and matching 401K Flexible work environment ability to work remote Flexible time off including volunteer time off vacation sick and 12-paid holidays Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters DEI work/life balance development authenticity collaboration wellness reward & recognition volunteering... the list goes on. Experian's people first approach is award-winning World's Best Workplaces 2024 (Fortune Top 25) Great Place To Work in 24 countries and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why. Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range individual pay is determined by work location and additional factors such as job-related skills experience and education. You will be also eligible for a variable pay opportunity. Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal state and local law including protected veterans and individuals with disabilities. Innovation is an important part of Experian's DNA and practices and our inclusive workforce allows everyone to succeed and bring their whole self to work. If you have a disability or special need that requires accommodation please let us know at the earliest opportunity. This is a remote position.

UPMC Health Plan is seeking a skilled and motivated MLOps Engineer to join our AI Solutions team. In this role you will be responsible for designing building and maintaining the infrastructure and tools that enable the deployment monitoring and scaling of machine learning models in production. You will work closely with data scientists software engineers and Cloud Engineering teams to streamline the ML lifecycle and ensure robust secure and efficient model operations. Responsibilities: Develop and maintain CI/CD pipelines for machine learning workflows including model training validation deployment and monitoring. Collaborate with data scientists to productionize ML models and ensure reproducibility and scalability. Design and implement model versioning model registry and automated retraining strategies. Monitor model performance and data drift in production environments and implement alerting and rollback mechanisms. Optimize infrastructure for cost performance and reliability using cloud-native tools and services (e.g. AWS Azure GCP). Ensure compliance with data governance security and privacy standards throughout the ML lifecycle. Automate data ingestion feature engineering and model evaluation processes. Contribute to the development of internal tools and frameworks to support experimentation and deployment. Document best practices and provide guidance to cross-functional teams on MLOps principles. Masters degree in Computer Science Engineering or a related field or Bachelors in related fields with 5+ years relevant professional experience. 3+ years of experience in MLOps DevOps or ML Engineering roles. Preference will be given to those with MLOps experience. 3 years relevant work experience after completion of terminal degree is highly preferred. Experience deploying and building data science and machine learning solutions. Proficiency with ML lifecycle tools and orchestration frameworks. Hands on experience with cloud platforms (Azure preferred) Solid understanding of CI/CD principles. Familiarity with drift monitoring logging and alert frameworks. Licensure Certifications and Clearances: Act 34 UPMC is an Equal Opportunity Employer/Disability/Veteran

Position : MLOps Engineer - Remote Location : San Diego CA Duration : 10 Months Total Hours/week : 40.00 1st Shift Client : Medical Devices Company Job Category : Technical/Engineering Level of Experience : Senior Level Employment Type : Contract on W2 (Need US Citizens or GC Holders or GC EAD or OPT or EAD or CPT) Job Description We're seeking an experienced MLOps Engineer to lead the operationalization of our Machine Learning workloads. As a key team member you'll be responsible for designing building and maintaining infrastructure required for efficient development deployment and monitoring of machine learning workloads. Your close collaboration with data scientists will ensure that our models are reliable scalable and performing optimally. This role requires expertise in automating ML workflows enhancing model reproducibility and ensuring continuous integration and delivery. Responsibilities Architect for scalable cost-efficient reliable and secure ML solution. Design implement and deploy ML solutions in AWS. Select and justify appropriate ML technology within AWS and Identify appropriate AWS services to implement ML solutions. Design build and maintain infrastructure required for efficient development deployment and monitoring of machine learning models. Implement CI/CD pipelines for machine learning applications to ensure smooth development and deployment processes. Collaborate with data scientists to understand and implement requirements for model serving versioning and reproducibility. Monitor and optimize model performance in production identifying and resolving issues proactively to ensure optimal results. Automate repetitive tasks to improve efficiency and reduce the risk of human error in MLOps workflows. Maintain documentation and provide training to team members on MLOps best practices ensuring knowledge sharing and collaboration within the team. Stay updated with the latest developments in MLOps tools technologies and methodologies to remain current and effective in your role. Qualifications Bachelor's or Master's degree in Computer Science Engineering or a related field. 3+ years of experience in MLOps DevOps or related fields. Strong programming skills in Python GoLang with experience in other languages such as Java C++ or Scala being a plus. Experience with ML frameworks such as TensorFlow PyTorch and/or scikit-learn. Proficiency with CI/CD tools such as Github Actions. Hands-on experience with AWS. Familiarity with containerization and orchestration tools like Docker and Kubernetes. Knowledge of infrastructure-as-code tools such as AWS CDK and Cloudformation. Strong understanding of machine learning lifecycle including data preprocessing model training evaluation and deployment. Excellent problem-solving skills and the ability to work independently as well as part of a team. Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders. Preferred Qualifications AWS Certified Machine Learning - Specialty Experience with feature stores model registries and monitoring tools such as MLflow Tecton or Seldon. Familiarity with data engineering tools such as AWS EMR Glue and Apache Spark. Knowledge of security best practices for machine learning systems. Experience with A/B testing and model performance monitoring.