Senior Machine Learning Engineer (AI Foundations)
$161.8k - $184.6kCapital One Bank
Senior Machine Learning Engineer (AI Foundations) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to 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, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Capital One is accelerating the adoption of state of the art AI research to create simpler, safer banking experiences for over 100 million customers. The AI Foundations team spearheads this mission by developing advanced LLMs and autonomous agentic systems capable of complex reasoning and real world problem solving. Their comprehensive research framework prioritizes foundational model architecture, operational efficiency, and responsible AI practices to ensure all systems are trustworthy and scalable. What You’ll Do: 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 Basic Qualifications: Bachelor’s Degree At least 4 years of experience programming with Python, Scala, or Java 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 frameworks (scikit‑learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems
- years of experience with data gathering and preparation for ML models
- years of experience developing performant, resilient, and maintainable code
$229.9k - $262.4k
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...creating responsible and reliable AI systems, changing banking... ...an industry leader in using machine learning to create real‑time,... ...world‑class applied science and engineering teams to deliver our industry... ..., powered by resilient data foundations, production‑grade ML and GenAI...SeniorFoundationRemote jobLocal areaFlexible hours$161.8k - $184.6k
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