Capital One Canada is looking for a Machine Learning Engineer to join an Agile team focused on productionizing machine learning applications and systems at scale. You will be involved in the technical design, development, and implementation of ML applications using current and emerging technology platforms.
What You'll Do
- Design, build, and deliver ML models and components that solve business problems in collaboration with Product and Data Science teams.
- Inform ML infrastructure decisions using your understanding of modeling techniques, including model choice, data and feature selection, training, 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 software that enables big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures and platforms 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 deployment.
- Ensure code is well-managed to reduce vulnerabilities, models are well-governed, and ML follows Responsible and Explainable AI best practices.
What We're Looking For
- Bachelor’s Degree.
- At least 4 years of experience programming with Python, Scala, or Java (internship experience does not apply).
- At least 3 years of experience 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.
- Contribution to open source ML software.
- Authored or 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
- Health, financial, and other benefits that support total well-being.
- Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
- Compensation ranges: McLean, VA: $161,800 - $184,600; New York, NY: $176,500 - $201,400.
Work Mode
This is a local-city role based in McLean, VA or New York, NY.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
