AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)
$230k - $262k • San Jose, CA • Full-time
Posted 11d ago
About the job
Capital One is building responsible and reliable AI systems to transform banking. Leveraging extensive experience in machine learning and investments in technology, the company aims to be at the forefront of AI adoption. This role is within the Intelligent Foundations and Experiences (IFX) team, which is central to realizing this vision by advancing AI science and engineering, and deploying proprietary solutions that deliver value to millions of customers. The team's AI models and platforms empower other departments to enhance their products responsibly and scalably. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve customers and businesses.
Responsibilities
- Partner with cross-functional teams to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems.
- Design, implement, and optimize multi-model orchestration pipelines, integrating LLMs, vector search, and domain-specific models.
- Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
- Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards.
- Mentor AI engineers, fostering cross-domain learning and elevating organizational technical maturity.
Requirements
- Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, OR a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies.
- At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
- Experience leading development of AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
- 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience designing, developing, delivering, and supporting complex AI systems.
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Experience in building agentic AI systems and agentic workflows.
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production.
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
- Experience architecting and integrating heterogeneous AI systems (including rule-based, retrieval-augmented, and generative components) into unified production pipelines.
- Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop.