Manager, Machine Learning Engineering (People Leader)

Center 1 (19052), United States of America, McLean, Virginia Manager, Machine Learning Engineering (People Leader) The Apollo team at Capital One aims to provide a 360-degree view of every business in the US, powered by cutting-edge entity resolution capabilities. Entity resolution refers to the ability to resolve/link different pieces of information gathered to a specific entity with a high degree of accuracy. The Apollo organization is a lean, purpose-driven group that's expanding rapidly and seeking strong engineering talent. Within the Apollo sphere, there are opportunities for hands-on engineering leaders to manage ML operation systems, Feature Engineering, and Model development in partnership with data scientists, powering the customer experiences across Apollo’s product offerings. As a Machine Learning Engineer (MLE) manager, you'll lead a part of an Agile team focused on productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, ensuring the high performance and availability of our machine learning applications. You'll have the chance to continuously learn and implement the latest innovations and best practices in machine learning engineering. Responsibilities in the role: The MLE role intersects with many disciplines, such as ML Ops, and Data Engineering. In this role, you're expected to perform many ML engineering activities, which may include the following: - Collaborate with a cross-functional team of data scientists, software engineers, product managers, and designers to deliver AI-powered products that customers love. - Make informed ML infrastructure decisions based on your understanding of ML modeling techniques and issues. - Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployments. - Retrain, maintain, and monitor models in production. - Construct optimized big data pipelines to feed ML models. - 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. Basic Qualifications: - Bachelor’s degree - At least six years of experience designing and building data-intensive solutions using distributed computing (Internship experience doesn't count) - At least four years of experience programming with Python, Scala, or Java - At least two years of experience building, scaling, and productionizing ML systems - At least two years of people manager experience Preferred Qualifications: - Master's or Doctoral degree in computer science, electrical engineering, mathematics, or a related field - Three+ years of experience building production-ready data pipelines that feed ML models - Three+ years of job experience with an industry-recognized ML framework such as Scikit-learn, PyTorch, Dask, Spark, or TensorFlow - Two+ years of experience in big data technologies - Experience with Graph Databases such as Neptune and Neo4j - Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform At this time, Capital One will not sponsor a new applicant for employment authorization for this position. New York City (Hybrid On-Site): Manager, Machine Learning Engineering salary range: $197,400 - $225,300 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 their offer letter. This role is also eligible for performance-based incentive compensation, which may include cash bonuses and/or long term incentives. 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 wellbeing. Please learn more on the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.