Technologies:
Python, Docker, Go, C++, AWS, Java, Azure

Excellent communication skills (written and verbal)
Working knowledge of cloud technology
Familiarity with object-oriented programming
Advanced working knowledge of PyTorch or TensorFlow
Familiarity with computer science/software engineering concepts, including common data structures and algorithms
Familiarity with Docker containers
Experience implementing state-of-the-art models from research papers
Solid background in deep learning: layer details, loss functions, accuracy metrics, optimization, etc.

Collaborate with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, similarity search, guardrails, and more.
Leverage a broad stack of Open Source and SaaS AI technologies, such as AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, and PyTorch.
Introduce optimization techniques to enhance large-scale AI systems in terms of scalability, cost, latency, and throughput.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.

Bachelor’s degree in Computer Science, Engineering, or AI with at least 8 years of experience developing AI/ML algorithms, or Master’s degree with at least 6 years of experience in AI/ML development.
2-5 years of programming experience with Python, Go, Scala, or Java.
2+ of experience deploying scalable AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
Passion for machine learning and a desire to stay up-to-date with the latest developments in the field.
Ability to collaborate effectively with colleagues from different backgrounds and disciplines.

AI / ML Cloud Engineer

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