| 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. #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 |