Design, build, and/or deliver ML models and components that solve real-world business problems
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more
Construct optimized data pipelines to feed ML models
Design, develop, test, deploy, and support AI software components including large language model inference, similarity search, model evaluation, experimentation, governance, and observability
Invent and introduce state-of-the-art LLM optimization techniques
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One

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)
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (Preferred)
2+ years of experience with data gathering and preparation for ML models (Preferred)

Lead Machine Learning Engineer

Key skills