Join Capital One Canada as a Senior Machine Learning Engineer. You will be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. Your role involves the technical design, development, and implementation of ML solutions.
What You'll Do
- Design, build, and deliver ML models and components in collaboration with Product and Data Science teams to solve business problems.
- Inform ML infrastructure decisions using your understanding of modeling techniques.
- Solve complex problems by writing and testing application code, developing and validating models, and automating tests and deployment.
- Collaborate within a cross-functional Agile team to create software for big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage CI/CD best practices, including test automation and monitoring, for successful model and code deployment.
- Ensure code is well-managed to reduce vulnerabilities, models are well-governed for risk, and ML follows Responsible and Explainable AI best practices.
What We're Looking For
- Bachelor’s Degree.
- At least 4 years of programming experience with Python, Scala, or Java (Internship experience does not apply).
- At least 3 years designing and building data-intensive solutions using distributed computing.
- At least 2 years of on-the-job experience with an industry-recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).
- At least 1 year of experience productionizing, monitoring, and maintaining models.
Nice to Have
- 1+ years of experience building, scaling, and optimizing ML systems.
- 1+ years of experience with data gathering and preparation for ML models.
- 2+ years of experience developing performant, resilient, and maintainable code.
- Experience developing and deploying ML solutions in a public cloud (AWS, Azure, or Google Cloud Platform).
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
- 3+ years of experience with distributed file systems or multi-node database paradigms.
- Contributed to open source ML software.
- Authored/co-authored a paper on an ML technique, model, or proof of concept.
- 3+ years of experience building production-ready data pipelines that feed ML models.
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
Technical Stack
- Languages: Python, Scala, Java
- ML Frameworks: scikit-learn, PyTorch, Dask, Spark, TensorFlow
- Cloud Platforms: AWS, Azure, Google Cloud Platform
Team & Environment
You will be part of an Agile team.
Benefits & Compensation
- Comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well-being.
- Compensation ranges:
- Chicago, IL: $147,100 - $167,900
- McLean, VA: $161,800 - $184,600
- Plano, TX: $147,100 - $167,900
- Richmond, VA: $147,100 - $167,900
Work Mode
This role follows a local-city work mode, based in one of the following locations: Chicago, IL; McLean, VA; Plano, TX; Richmond, VA.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
