Machine Learning Engineer at Capital One responsible for productionizing ML applications in Agile teams. Focused on ML architectural design, coding, and maintaining high availability of models.
About the role
- AI/ML Engineer responsible for designing, building, and operating ML solutions in production. Collaborating with data teams to deliver measurable impact using advanced analytics.
Responsibilities
- Lead full lifecycle AI/ML system development in Palantir Foundry, including data pipeline integration, feature engineering, model implementation, deployment, and production monitoring
- Design, develop, and optimize machine learning models and algorithms for performance, scalability, and reliability
- Collaborate with data scientists and engineers to transition models from research and experimentation into production systems
- Build and maintain model deployment, versioning, and monitoring workflows
- Integrate AI/ML solutions into existing platforms and business processes
- Evaluate and apply emerging AI/ML technologies where they provide clear business value
- Ensure robustness, maintainability, and performance of deployed AI/ML systems in operational environments
Requirements
- 5+ years of hands-on experience building, deploying, and maintaining AI/ML systems end-to-end in production environments
- Proficiency in programming languages such as Python, R, or Java
- Expertise in AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras)
- Experience delivering AI/ML solutions in Palantir Foundry (e.g., Code Workbooks, Code Authoring, pipelines, model operationalization)
- Strong understanding of machine learning techniques, including supervised and unsupervised learning and deep learning approaches
- Experience with model deployment, monitoring, and MLOps tooling (e.g., Docker, Kubernetes, MLflow or similar)
- Experience working with large-scale data systems and cloud or hybrid environments
- Strong analytical and problem-solving skills, with the ability to work with complex systems and datasets
- Excellent communication skills to explain technical concepts to non-technical stakeholders and collaborate across teams
- 5+ years of hands-on experience delivering AI/ML solutions end-to-end in production environments, including data ingestion, feature engineering, model development, deployment, and ongoing monitoring
- 3+ years of practical experience building and operationalizing AI/ML systems in Palantir Foundry (e.g., Code Workbooks, Code Authoring, pipelines, model operationalization)
- Advanced degree in Artificial Intelligence, Machine Learning, Data Science, or related fields
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