Lead Machine Learning Engineer – Manager IC

Role Overview

• Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers.
• Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
• Fine-tune, develop and evaluate machine learning and foundation models.
• Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities.
• Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One.
• Leverage a broad stack of Open Source and SaaS AI technologies.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
• Retrain, maintain, and monitor models in production.
• Construct optimized 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.

Requirements

• Bachelor’s Degree
• At least 6 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 2 years of experience building, scaling, and optimizing ML systems
• Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (Preferred)
• 7+ years of experience designing, developing, delivering, and supporting AI services at scale (Preferred)
• 3+ years of experience building production-ready data pipelines that feed ML models (Preferred)
• 3+ 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 AI and ML algorithms or technologies using Python (Preferred)
• 2+ years of experience with Retrieval Augmented Generation (RAG) (Preferred)
• 2+ years of experience with data gathering and preparation for ML models (Preferred)
• 2+ years of people leader experience (Preferred)
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation (Preferred)
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance (Preferred)
• Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion (Preferred)
• Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure (Preferred)

Tech Stack

• AWS
• Azure
• Cloud
• Java
• Open Source
• Python
• PyTorch
• Scala
• Scikit-Learn
• Spark
• Tensorflow

Benefits

• Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being