Senior Manager, Software Engineering, Machine Learning

November 13

Apply Now
Logo of Capital One

Capital One

Banking • Fintech • Finance

Capital One is a leading financial services company that specializes in offering credit cards, auto loans, banking, and savings accounts. With a focus on innovation and technology, Capital One aims to change banking for good by providing customer-friendly solutions and fostering a diverse and inclusive workforce. The company is known for its commitment to creating a positive impact in the banking industry through advanced digital tools and customer service excellence.

10,000+ employees

🏦 Banking

💳 Fintech

💸 Finance

💰 Post-IPO Equity on 2023-05

📋 Description

• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, 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 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 • Use programming languages like Python, Scala, or Java

🎯 Requirements

• Bachelor’s degree • At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) • At least 4 years of experience programming with Python, Scala, or Java • At least 3 years of experience building, scaling, and optimizing ML systems • At least 2 years of experience leading teams developing ML solutions • At least 4 years of people management experience • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field preferred • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow preferred • 3+ years of experience developing performant, resilient, and maintainable code preferred • 3+ years of experience with data gathering and preparation for ML models preferred • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform preferred • 3+ years of experience building production-ready data pipelines that feed ML models preferred • Ability to communicate complex technical concepts clearly to a variety of audiences preferred • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents preferred

🏖️ Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well-being

Apply Now

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