Top AI & Machine Learning Jobs in Boston, MA

In this role, you will lead AI projects, collaborating with cross-functional teams to develop and deploy advanced AI solutions, focusing on LLM inference and model optimization.

The Applied Researcher II will work on developing AI foundation models, partner with cross-functional teams, and engage in impactful research to enhance customer experiences using advanced AI techniques.

As a Sr. Lead AI Engineer, you will design, develop, and manage AI software components, working with cross-functional teams to advance AI applications at Capital One.

Lead AI Engineer responsible for creating and deploying AI solutions, collaborating with cross-functional teams to innovate AI-powered banking products, and driving the technical vision for foundational AI systems.

The Senior Distinguished AI Engineer at Capital One will develop AI-powered products, optimize large-scale AI systems, and mentor engineering teams, driving advancements in AI and ML for better customer experiences.

The Lead AI Engineer will develop AI solutions, partner with cross-functional teams, and optimize large-scale production AI systems using various technologies.

Lead AI Engineer to design, build, deploy, and support production-scale vision and foundation-model components (training, inference, vector search, guardrails, evaluation, observability). Partner with cross-functional teams, optimize LLM training/inference for cost/latency/throughput, and help set the technical vision and roadmap for foundational AI systems at Capital One.

As a Senior Lead AI Engineer, you will design and develop advanced AI systems, collaborate with cross-functional teams, and introduce innovative AI techniques while mentoring others.

The Applied Researcher I will partner with teams to deliver AI products, leverage technologies to analyze data, and build foundation models. This role includes engaging in applied research and translating technical findings into business goals.

Lead design, build, deploy, and maintain production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to create data pipelines, retrain and monitor models, and apply responsible, explainable AI practices while contributing technical vision and roadmap for AI solutions.