Lead Machine Learning Engineer
3 days ago
Capital One is seeking a highly skilled Lead Machine Learning Engineer to join our team. As a key member of our Agile team, you will be responsible for designing, building, and delivering machine learning applications using existing and emerging technology platforms.
Key Responsibilities:
- Design and develop machine learning models and components that solve real-world business problems.
- Collaborate with Product and Data Science teams to inform ML infrastructure decisions.
- 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.
Requirements:
- Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
- At least 6 years of experience designing and building data-intensive solutions using distributed computing.
- 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 related 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.
- 2+ years of people leader experience.
- 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation.
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
What We Offer:
- Competitive salary range: $201,400 - $229,900 per year.
- Performance-based incentive compensation.
- A comprehensive, competitive, and inclusive set of health, financial, and other benefits.
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