Senior Distinguished AI Engineer

What you'd actually do

1. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
2. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
3. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
4. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Skills

What the JD emphasized

• deliver AI-powered products
• foundation model training
• large language model inference
• similarity search
• guardrails
• model evaluation
• experimentation
• governance
• observability
• LLM optimization techniques
• scalability
• cost
• latency
• throughput
• complex enterprise AI systems
• architecting, designing, developing, integrating, delivering, and supporting complex enterprise 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, 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

Other signals

• foundation model training
• large language model inference
• similarity search
• guardrails
• model evaluation
• experimentation
• governance
• observability
• LLM optimization techniques
• scalability
• cost
• latency
• throughput