AI Engineer 5 (MLXT)
$230k - $262k • McLean, VA • Full-time
Posted 1mo ago
About the job
Capital One is at the forefront of leveraging AI to transform banking, creating responsible and reliable AI systems that enhance customer experiences. The Intelligent Foundations and Experiences (IFX) team is central to this vision, building and deploying proprietary AI solutions that deliver value to millions of customers. This role involves partnering with cross-functional teams to deliver AI-powered products, designing and supporting AI software components, and leveraging a broad stack of AI technologies. You will invent and introduce state-of-the-art foundation model optimization techniques, contribute to the technical vision of foundational AI systems, and design/implement multi-model orchestration pipelines. The ideal candidate is deeply technical, passionate about AI research, and thrives on solving complex, undefined problems.
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, similarity search, guardrails, model evaluation, 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 AI systems.
- Contribute to the technical vision and 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 for AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
- Lead team design councils or 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 applying 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 review processes.