Category Engineering Experience Manager Primary Address Richmond Virginia Overview Lead Machine Learning Engineer Shopping - Feed (Remote)Interested in joining a dynamic remote first engineering team in a fast-paced environment full of greenfield problem-solving? Then Capital One Shopping might be the place for you. Join us in supporting a growth-stage line of business with a startup mindset as we build technology to save our customers money. As a Capital One Machine Learning Engineer (MLE) you'll be part of a fast moving highly collaborative Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll drive and deliver the detailed technical designs development and implementation of machine learning applications using existing and emerging technology platforms. You’ll be a leader of machine learning architectural design develop and review model and application code and ensure high availability and performance of our machine learning applications. You'll contribute to researching our next generation of models and recommendation systems to deliver value to our customers. You’ll mentor junior developers and serve as a technical bridge between product partners. You will use tools like Docker Nomad SQL Python Pytorch Transformers language models and other statistical tools. This is more than just a job it's an opportunity to be part of a collaborative and forward-thinking community where your contributions will make a significant impact in an ever-dynamic tech landscape. Join us as we push boundaries and redefine the future of our industry. What you’ll do in the role: The MLE role overlaps with many disciplines such as Ops Modeling and Data Engineering. In this role you'll be expected to perform many ML engineering activities including one or more of the following: Design build and/or deliver ML models and components that solve real-world business problems while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues including choice of model data and feature selection model training hyperparameter tuning dimensionality bias/variance and validation). Solve complex problems by writing and testing application code developing and validating ML models and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain maintain and monitor models in production. Leverage or build cloud-based architectures technologies and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices including test automation and monitoring to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities models are well-governed from a risk perspective and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python Scala or Java. Design and research new models using data scientist experience/expertise Basic Qualifications: Bachelor’s degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python Scala or Java At least 2 years of experience building scaling and optimizing ML systems Preferred Qualifications: Master's or doctoral degree in computer science electrical engineering mathematics or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn PyTorch Dask Spark or TensorFlow 2+ years of experience developing performant resilient and maintainable code 2+ years of experience with data gathering and preparation for ML models At this time Capital One will not sponsor a new applicant for employment authorization or offer any immigration related support for this position (i.e. H1B F-1 OPT F-1 STEM OPT F-1 CPT J-1 TN or another type of work authorization). The minimum and maximum full-time annual salaries for this role are listed below by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $175800 - $200700 for Lead Machine Learning Engineer Richmond VA: $175800 - $200700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive competitive and inclusive set of health financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status exempt or non-exempt status and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE including disability/vet) committed to non-discrimination in compliance with applicable federal state and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries including to the extent applicable Article 23-A of the New York Correction Law San Francisco California Police Code Article 49 Sections 4901-4920 New York City’s Fair Chance Act Philadelphia’s Fair Criminal Records Screening Act and other applicable federal state and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position and you require an accommodation please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process please send an email to Careers@capitalone.com Capital One does not provide endorse nor guarantee and is not liable for third-party products services educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). This carousel contains a column of headings. Selecting a heading will change the main content in the carousel that follows. Use the Previous and Next buttons to cycle through all the options use Enter to select. This carousel shows one item at a time. Use the preceding navigation carousel to select a specific heading to display the content here. How We Hire We take finding great coworkers pretty seriously. Step 1 Apply It only takes a few minutes to complete our application and assessment. Step 2 Screen and Schedule If your application is a good match you’ll hear from one of our recruiters to set up a screening interview. Step 3 Interview(s) Now’s your chance to learn about the job show us who you are share why you would be a great addition to the team and determine if Capital One is the place for you. Step 4 Decision The team will discuss — if it’s a good fit for us and you we’ll make it official! How to Pick the Perfect Career Opportunity Overwhelmed by a tough career choice? Read these tips from Devon Rollins Senior Director of Cyber Intelligence to help you accept the right offer with confidence. Your wellbeing is our priority Our benefits and total compensation package is designed for the whole person. Caring for both you and your family. #### Healthy Body Healthy Mind You have options and we have the tools to help you decide which health plans best fit your needs. #### Save Money Make Money Secure your present plan for your future and reduce expenses along the way. #### Time Family and Advice Options for your time opportunities for your family and advice along the way. It’s time to BeWell. Career Journey Here’s how the team fits together. We’re big on growth and knowing who and how coworkers can best support you.

Lensa is the leading career site for job seekers at every stage of their career. Our client Cisco is seeking professionals. Apply via Lensa today! Machine Learning Engineer (MLE) Artificial Intelligence Join us as we pursue our disruptive new vision to make machine data accessible usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk we’re committed to our work customers having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey! Role As a Machine Learning Engineer in the Artificial Intelligence group you will be responsible for developing the core AI/ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency. You will collaborate with cross-functional teams mentor junior team members and help drive the engineering roadmap of the area. Responsibilities The responsibilities of this role include: Development of the AI/ML platform and infrastructure that drives our product’s key ML use cases in the cybersecurity and observability domains. Collaborate closely with software engineers applied scientists and product managers to integrate generative AI solutions into our products and services. Stay up to date with the latest developments in the field of AI/ML and ensure that these advancements are properly incorporated into our technology roadmap. Actively participate in cross-functional discussions and strategic decisions related to AI directions and product roadmaps. Requirements Knowledge Skills and Abilities: Bachelor's or Master's degree in Computer Science Engineering or a related field with at least 3+ years of industry experience. Experience with containerization and orchestration tools (e.g. Docker Kubernetes). Experience with model deployment and serving into production environments Knowledge of version control systems especially Git. Knowledge of CI/CD principles and tools. Familiarity with cloud platforms (AWS GCP Azure) and serverless architecture. Experience with MLOps platforms such as MLflow or Kubeflow. Previous experience working in cross-functional teams and collaborating with data scientists and DevOps teams. Excellent problem-solving skills and the ability to troubleshoot complex issues. Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. Splunk is an Equal Opportunity Employer: At Splunk we believe creating a culture of belonging isn’t just the right thing to do it’s also the smart thing. We prioritize diversity equity inclusion and belonging to ensure our employees are supported to bring their best most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race religion color national origin ancestry sex gender gender identity gender expression sexual orientation marital status age physical or mental disability or medical condition genetic information veteran status or any other consideration made unlawful by federal state or local laws. We consider qualified applicants with criminal histories consistent with legal requirements. Note Base Pay Range SF Bay Area Seattle Metro and New York City Metro Area Base Pay Range: $146400.00 - 201300.00 per year California (excludes SF Bay Area) Washington (excludes Seattle Metro) Washington DC Metro and Massachusetts Base Pay Range: $131760.00 - 181170.00 per year All other cities and states excluding California Washington Massachusetts New York City Metro Area and Washington DC Metro Area. Base Pay Range: $117120.00 - 161040.00 per year Splunk provides flexibility and choice in the working arrangement for most roles including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer the base pay will vary based on factors such as work location as set out above as well as the knowledge skills and experience of the candidate. In addition to base pay this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards. Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a competitive benefits package which includes medical dental vision a 401(k) plan and match paid time off and much more! Learn more about our next-level benefits at https://splunkbenefits.com .

One of my direct clients a Decision Intelligence Platform (Healthcare) is looking for a Machine Learning Engineer. Hybrid mode - Twice a month travel to Texas Skills - Machine Learning Apache Spark Hadoop and Teradata Duration - 6+ months long term C2C Rate - DOE Client details will be shared post technical call We are seeking an experienced Machine Learning Engineer for 6-month contract engagement. This is a remote role with occasional travel to the client site in Dallas TX. Taking applications only from candidates who have 5-10 years of Coding experience with at least 2 years in Machine Learning Data Analysis and Big Data overall 10+ years. Technical Skills Strong expertise in Machine Learning – both supervised and unsupervised methods Hands-on experience with Apache Spark and large-scale data processing Knowledge and working experience with Hadoop and Teradata Experience building and deploying scalable ML models in production environments Non-Technical Skills Excellent communication and client presentation skills Ability to present solutions and insights to clients effectively Collaborative mindset with the ability to work cross-functionally in remote settings Bachelor’s degree in Computer Science Information Technology or a related field (or equivalent experience). The salary range for this role is $110K to $130K. For C2C/W2 rates please contact the recruiter. In addition to other benefits Accion Labs offers a comprehensive benefits package with Accion covering 65% of the medical dental and Vision Premiums for employees their spouses and dependent children enrolling in the Accion-provided plans.

Lensa is the leading career site for job seekers at every stage of their career. Our client Cisco is seeking professionals. Apply via Lensa today! Machine Learning Engineer (MLE) Artificial Intelligence Join us as we pursue our disruptive new vision to make machine data accessible usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk we’re committed to our work customers having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey! Role As a Machine Learning Engineer in the Artificial Intelligence group you will be responsible for developing the core AI/ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency. You will collaborate with cross-functional teams mentor junior team members and help drive the engineering roadmap of the area. Responsibilities The responsibilities of this role include: Development of the AI/ML platform and infrastructure that drives our product’s key ML use cases in the cybersecurity and observability domains. Collaborate closely with software engineers applied scientists and product managers to integrate generative AI solutions into our products and services. Stay up to date with the latest developments in the field of AI/ML and ensure that these advancements are properly incorporated into our technology roadmap. Actively participate in cross-functional discussions and strategic decisions related to AI directions and product roadmaps. Requirements Knowledge Skills and Abilities: Bachelor's or Master's degree in Computer Science Engineering or a related field with at least 3+ years of industry experience. Experience with containerization and orchestration tools (e.g. Docker Kubernetes). Experience with model deployment and serving into production environments Knowledge of version control systems especially Git. Knowledge of CI/CD principles and tools. Familiarity with cloud platforms (AWS GCP Azure) and serverless architecture. Experience with MLOps platforms such as MLflow or Kubeflow. Previous experience working in cross-functional teams and collaborating with data scientists and DevOps teams. Excellent problem-solving skills and the ability to troubleshoot complex issues. Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. Splunk is an Equal Opportunity Employer: At Splunk we believe creating a culture of belonging isn’t just the right thing to do it’s also the smart thing. We prioritize diversity equity inclusion and belonging to ensure our employees are supported to bring their best most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race religion color national origin ancestry sex gender gender identity gender expression sexual orientation marital status age physical or mental disability or medical condition genetic information veteran status or any other consideration made unlawful by federal state or local laws. We consider qualified applicants with criminal histories consistent with legal requirements. Note Base Pay Range SF Bay Area Seattle Metro and New York City Metro Area Base Pay Range: $146400.00 - 201300.00 per year California (excludes SF Bay Area) Washington (excludes Seattle Metro) Washington DC Metro and Massachusetts Base Pay Range: $131760.00 - 181170.00 per year All other cities and states excluding California Washington Massachusetts New York City Metro Area and Washington DC Metro Area. Base Pay Range: $117120.00 - 161040.00 per year Splunk provides flexibility and choice in the working arrangement for most roles including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer the base pay will vary based on factors such as work location as set out above as well as the knowledge skills and experience of the candidate. In addition to base pay this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards. Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a competitive benefits package which includes medical dental vision a 401(k) plan and match paid time off and much more! Learn more about our next-level benefits at https://splunkbenefits.com .

Lensa is the leading career site for job seekers at every stage of their career. Our client Cisco is seeking professionals. Apply via Lensa today! Machine Learning Engineer (MLE) Artificial Intelligence Join us as we pursue our disruptive new vision to make machine data accessible usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk we’re committed to our work customers having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey! Role As a Machine Learning Engineer in the Artificial Intelligence group you will be responsible for developing the core AI/ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency. You will collaborate with cross-functional teams mentor junior team members and help drive the engineering roadmap of the area. Responsibilities The responsibilities of this role include: Development of the AI/ML platform and infrastructure that drives our product’s key ML use cases in the cybersecurity and observability domains. Collaborate closely with software engineers applied scientists and product managers to integrate generative AI solutions into our products and services. Stay up to date with the latest developments in the field of AI/ML and ensure that these advancements are properly incorporated into our technology roadmap. Actively participate in cross-functional discussions and strategic decisions related to AI directions and product roadmaps. Requirements Knowledge Skills and Abilities: Bachelor's or Master's degree in Computer Science Engineering or a related field with at least 3+ years of industry experience. Experience with containerization and orchestration tools (e.g. Docker Kubernetes). Experience with model deployment and serving into production environments Knowledge of version control systems especially Git. Knowledge of CI/CD principles and tools. Familiarity with cloud platforms (AWS GCP Azure) and serverless architecture. Experience with MLOps platforms such as MLflow or Kubeflow. Previous experience working in cross-functional teams and collaborating with data scientists and DevOps teams. Excellent problem-solving skills and the ability to troubleshoot complex issues. Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. Splunk is an Equal Opportunity Employer: At Splunk we believe creating a culture of belonging isn’t just the right thing to do it’s also the smart thing. We prioritize diversity equity inclusion and belonging to ensure our employees are supported to bring their best most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race religion color national origin ancestry sex gender gender identity gender expression sexual orientation marital status age physical or mental disability or medical condition genetic information veteran status or any other consideration made unlawful by federal state or local laws. We consider qualified applicants with criminal histories consistent with legal requirements. Note Base Pay Range SF Bay Area Seattle Metro and New York City Metro Area Base Pay Range: $146400.00 - 201300.00 per year California (excludes SF Bay Area) Washington (excludes Seattle Metro) Washington DC Metro and Massachusetts Base Pay Range: $131760.00 - 181170.00 per year All other cities and states excluding California Washington Massachusetts New York City Metro Area and Washington DC Metro Area. Base Pay Range: $117120.00 - 161040.00 per year Splunk provides flexibility and choice in the working arrangement for most roles including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer the base pay will vary based on factors such as work location as set out above as well as the knowledge skills and experience of the candidate. In addition to base pay this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards. Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a competitive benefits package which includes medical dental vision a 401(k) plan and match paid time off and much more! Learn more about our next-level benefits at https://splunkbenefits.com .

About Us We're a fast-moving startup on a mission to revolutionize the call centre industry using the power of AI and Large Language Models. We’re building intelligent systemsto enhance customer experience supercharge agent performance and drive operational excellence. Through advanced conversational AI we build systems that understand adapt and evolve with every conversation. Our platform powers decision-support tools and intelligent virtual agents helping call centers deliver faster smarter and more human customer service—where every interaction matters. As an ML Engineer you’ll design train and deploy models that not only empower better decisions and agent experiences—but also power the core intelligence behind real-time conversations. If you're a self-starter with a passion for deploying ML at scale and know how to get your hands dirty with LLMs we want you on our founding team. What You’ll Do Design build and deploy ML pipelines and LLM-powered applications from scratch. Fine-tune prompt and integrate state-of-the-art LLMs (e.g. OpenAI LLaMA Mistral). Apply advanced techniques like retrieval-augmented generation (RAG) tool use and embedding search. Collaborate with product and engineering to build AI-driven features for real-world call centre use cases (e.g. agent coaching auto summarization sentiment analysis). Own experiments end-to-end — from hypothesis to deployment — with minimal supervision. Optimize model inference (latency memory) for production-scale workloads. Set up scalable infrastructure for model training evaluation and continuous improvement. Help shape our ML/AI roadmap and contribute to technical strategy. What We’re Looking For 3+ years of experience as an ML Engineer Deep expertise in NLP and LLMs (e.g. transformers LoRA vector search prompt engineering). Strong Python skills and hands-on experience with frameworks like Hugging Face Transformers LangChain OpenAI PyTorch. Experience deploying ML models in production (e.g. APIs containers cloud-based services). Comfort working in early-stage/startup environments — fast pace lots of ambiguity high impact. Ability to work autonomously and make product-informed decisions with minimal oversight. Bonus Points For Experience in or knowledge of the call centre / contact centre space. Familiarity with voice-to-text models real-time analytics or conversation intelligence. MLOps experience (e.g. model versioning monitoring CI/CD). Prior experience with vector databases (e.g. FAISS Pinecone Weaviate). Why Join Us? Be part of a mission-driven startup from the ground up. Shape the future of AI in a high-impact real-world industry. Work remotely with flexibility and autonomy. Competitive compensation Job Type: Full-time Pay: Php42000.00 - Php45000.00 per month Schedule: On call Work Location: Remote

Position: Senior Java Full Stack Developer Location: Remote (Canada-based candidates only Vancouver BC preferred) We are hiring a Machine Learning Engineer to join our client’s team working at the intersection of advanced research and real-world applications. This fully remote role involves close collaboration with a global team of engineers and researchers to design develop and deploy machine learning models that contribute to the development of next-generation solutions. Responsibilities Collaborate on projects at the intersection of research and product with a diverse global team of researchers and engineers Develop new or improve existing ML models used in CAD software Process data and analyze feature extractions Design solutions based on error analysis Present results to collaborators and leadership Review relevant AI/ML literature to identify emerging methods technologies and best practices Minimum Qualifications BSc or MSc in Computer Science or equivalent industry experience At least 3-5 years of software development experience Proficiency with modern deep learning techniques (e.g. Network architectures regularization techniques learning techniques loss functions optimization strategies etc.) as well as frameworks (e.g. PyTorch Lightning Ray etc.) Experience with deploying machine learning models in production settings Experience with version control reproducibility and writing reusable testable code Experience with data modeling architecture and processing using varied data representations including 2D and 3D geometry Experience with cloud services and architectures (e.g. AWS Azure) Excellent written documentation skills to document code architectures and experiments Apply Now! and share your resume at hr@techedinlabs.com

Category Engineering Experience Director Primary Address McLean Virginia Overview Distinguished Engineer - Machine Learning Engineer - Consumer Engagement Platform (Remote Eligible) As a Distinguished Engineer at Capital One you will be a part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers machine learning experts product managers and people leaders. Our Distinguished Engineers are leading experts in their domains helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels helping optimize business outcomes while driving towards strong technology solutions. At Capital One we believe diversity of thought strengthens our ability to influence collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech mentoring internal talent and actively recruiting to keep building our community. Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies platforms and capability domains creating clear and concise communications code samples blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area but your input and impact will be sought and expected throughout the organization. The Customer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy for all of Capital One’s consumer products and organizations by providing well-managed self-service experimentation-driven and personalized product development. We are seeking a Distinguished Engineer to define architect and drive the implementation of our Personalization Platform. We are building a scalable infrastructure powering real-time hyper-personalized experiences from personalized home feeds to targeted messaging for millions of users across all of Capital One’s Financial products. If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams come join us in our mission to change banking for good. Key responsibilities: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics such as performance scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously balancing your time to maximize impact Act as a role model and mentor within the tech community helping to coach and strengthen the technical expertise and know-how of our engineering and product community What you’ll do: Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time personalized product experiences and multi-channel targeted user messaging across all Capital One products and services Partner cross-functionally with Product Data science Cloud infrastructure and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users Develop and maintain a flexible scalable rules engine to enable business-driven personalization logic allowing dynamic configuration of user segmentation targeting rules and real-time decisioning while integrating seamlessly with ML-driven recommendations. Design build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction model training testing deployment and both real-time and batch inference - ensuring high performance scalability and reliability. Architect low-latency event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data user behavior and contextual signals. Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows integration validation and testing systems and scalable monitoring & observability. Provide organizational technical leadership to influence architecture engineering standards cross-team strategies mentoring engineers and driving organization wide platform innovation. What you’ll bring: Proven expertise in designing implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging. Strong expertise in cloud-native engineering (GCP AWS or Azure) containerization (Docker Kubernetes) and automated deployment Proven leadership in driving platform strategy fostering cross-functional collaboration and influencing technical direction across the company Capital One is open to hiring a remote employee for this opportunity. Basic Qualifications Bachelor’s Degree At least 7 years of software engineering or software development experience At least 5 years of public cloud experience (AWS GCP Azure) At least 5 years of experience in Machine Learning and frameworks commonly used in recommendation systems (PyTorch Scikit-learn or TensorFlow) Preferred Qualifications: Bachelor's or Master's Degree in Computer Science or a related field 9+ years of experience in software engineering or software development experience 7+ years of experience with hands-on experience with Machine Learning (ML) Pipeline orchestration and workflow tools (Databricks Airflow or Kubeflow) 7+ years of experience with programming languages such as Python or Java 5+ years of experience developing and deploying Machine Learning systems at scale Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $239900 - $273800 for Distinguished Engineer McLean VA: $263900 - $301200 for Distinguished Engineer New York NY: $287800 - $328500 for Distinguished Engineer Plano TX: $239900 - $273800 for Distinguished Engineer Richmond VA: $239900 - $273800 for Distinguished Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive competitive and inclusive set of health financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status exempt or non-exempt status and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy childbirth or related medical conditions) race color age national origin religion disability genetic information marital status sexual orientation gender identity gender reassignment citizenship immigration status protected veteran status or any other basis prohibited under applicable federal state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries including to the extent applicable Article 23-A of the New York Correction Law San Francisco California Police Code Article 49 Sections 4901-4920 New York City’s Fair Chance Act Philadelphia’s Fair Criminal Records Screening Act and other applicable federal state and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position and you require an accommodation please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process please send an email to Careers@capitalone.com Capital One does not provide endorse nor guarantee and is not liable for third-party products services educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Step 1 Apply It only takes a few minutes to complete our application and assessment. Step 2 Screen and Schedule If your application is a good match you’ll hear from one of our recruiters to set up a screening interview. Step 3 Interview(s) Now’s your chance to learn about the job show us who you are share why you would be a great addition to the team and determine if Capital One is the place for you. Step 4 Decision The team will discuss — if it’s a good fit for us and you we’ll make it official!

Description Function: Engineering R&D → Data Science / Machine Learning / Operations ResearchAbout PulsePoint:PulsePoint is a fast-growing healthcare technology company (with adtech roots) using real-time data to transform healthcare. We help brands and agencies interpret the hard-to-read signals across the health journey and unify these digital determinants of health with real-world data to produce the most dimensional view of the customer. Our award-winning advertising platforms use machine learning and programmatic automation to seamlessly activate this data making marketing predictive analytics and decision support easy and instantaneous.Sr. Machine Learning Engineer AdTechAs a member of our Data Science Engineering team the Sr. Machine Learning Engineer AdTech will focus on optimizing real-time bidding strategies and auction mechanics to efficiently spend ad budgets and deliver against campaign targets. In addition to the above you will work with the greater Data Science/Engineering teams on:Analyzing and optimizing real-time bidding strategies and online auction mechanics Developing new or improving existing models of event predictions New feature engineering for multiple machine learning models:User embeddings and clustering fraud detection etc.Cross-device user identification cookieless mechanisms development Mining different data sources Supporting existing codebase for data integration and production support for our core models.Location: anywhere in the world (End days at around 2pm EST)Requirements:5 years minimum of experience in machine learning/data scienceKey Skills: Python Algorithms Optimisation NLP Data Mining Statistical Analysis Neural Networks Generalised Linear Regression Multiclass Classification Java RAdvanced knowledge of Python using standard DS packages (numpy/pandas/scikit etc.) Being able to optimize and speed-up code.3+ years of RTB Auction or similar online technologies.In addition to the above you’ll need to have strong knowledge in the following areas:Algorithms and Data Structures (e.g. sorting search tree binary heap trie time & mem complexities of algorithms)Probability and Statistics (e.g. hypothesis testing Markov process and its stationary distributions stochastic matrix and its properties Bayesian inference)ML & DS (e.g. dimensionality reduction geometry of PCA / SVD and of L1 / L2 regularisation Decision trees and their ensembles collaborative filtering Thompson sampling / MCMC Neural Networks etc.) Selection Process:1) Initial Screening Call (30 mins)2) Technical Pre-Screening Call with Principal Data Scientist (60 mins)4) Team Interview (around 4-5 hours total)5) WebMD/IB Sr. Tech Leader (30 mins)  WebMD and its affiliates is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race ancestry color religion sex gender age marital status sexual orientation gender identity national origin medical condition disability veterans status or any other basis protected by law.

Company Overview: Robonote.io is revolutionizing the call center industry with cutting-edge AI technology. Our innovative monitoring system processes voice text SMS and chat data to provide unprecedented insights into customer interactions. We leverage state-of-the-art AI solutions to enhance automation improve customer experience and drive operational efficiency. We are looking for a Machine Learning & Algorithmic Engineer with expertise in NLP LLM optimization and prompt engineering to help build and refine our AI-driven platform. If you're passionate about AI enjoy working on cutting-edge technologies and want to shape the future of AI-driven customer interactions we’d love to hear from you! Responsibilities: Optimize and fine-tune large language models (LLMs) for summarization labeling question answering and agentic AI capabilities. Train and enhance AI models to extract relevant insights from multimodal data sources (voice text chat and SMS). Design and refine prompt engineering strategies for various NLP tasks to ensure accurate and contextually aware outputs. Develop and maintain scalable ML pipelines for model training evaluation and deployment. Collaborate with data engineers software developers and product teams to integrate AI solutions into our platform. Requirements: Must-Have Skills: ✅ 4+ years of experience in Machine Learning ✅ Proven experience in LLM fine-tuning optimization and deployment ✅ Expertise in prompt engineering for AI-driven applications ✅ Strong background in machine learning deep learning and NLP ✅ Proficiency in Python with experience in key ML libraries: NumPy Pandas SciPy scikit-learn PyTorch or TensorFlow Hugging Face Transformers ✅ Familiarity with data versioning and MLOps tools ✅ Strong problem-solving skills and the ability to work autonomously in a remote setting Nice-to-Have Skills: ➕ Experience with vector databases for RAG applications ➕ Background in agentic AI development for conversational agents ➕ Familiarity with cloud platforms like AWS GCP or Azure for model deployment ➕ Knowledge of C++ for performance optimization What We Offer: ✅ Fully remote position with flexible working hours ✅ Opportunity to work with cutting-edge AI technologies ✅ Collaborative and fast-paced work environment ✅ The chance to make a significant impact in a rapidly growing AI company Reach our Talent Partner on patricia@robonote.io if you're ready to take ownership of your career and integrate new features and become part of an AI-focused and innovative team!