Top AI & Machine Learning Jobs in Boston, MA

As a Lead AI Engineer at Capital One, you will design and develop AI systems, collaborate with cross-functional teams, and optimize AI solutions for performance and scalability.

The role involves leading AI research projects, building AI foundation models, collaborating with engineering teams, and mentoring applied scientists to enhance customer interactions through AI.

Lead the development of AI software components for Capital One, including model training, inference, and system optimization. Collaborate with cross-functional teams to deliver groundbreaking AI solutions, ensuring quality and scalability while mentoring junior team members.

The role involves developing AI foundation models, collaborating with cross-functional teams, and conducting applied research to enhance customer experiences using advanced AI techniques.

The role involves partnering with cross-functional teams to design, develop, and deploy AI software solutions, focusing on large language models and AI optimization techniques.

Lead design, development, deployment, and optimization of large-scale AI/ML systems (training, inference, orchestration, observability). Collaborate cross-functionally to build responsible, scalable generative AI and agentic platforms, improve performance and cost, and shape long-term ML systems roadmap.

Partner with teams to deliver AI-powered products, build foundation models, and conduct applied research to enhance customer experiences.

Lead design, build, deploy, and support scalable, responsible AI systems (foundation model training, LLM inference, similarity search, guardrails, observability). Collaborate with cross-functional teams, optimize model performance and cost, and shape technical vision and roadmap for foundational AI platform services.

Design, build, deploy, and maintain production-scale ML models and pipelines. Collaborate with product and data science teams to architect ML systems, implement model training and monitoring, optimize performance and reliability, and apply Responsible/Explainable AI practices using cloud and distributed computing technologies.

Lead an AI engineering team to design, build, deploy, and support foundation-model and LLM-based systems. Oversee model training, inference, similarity search, guardrails, evaluation, observability, and scalability optimizations. Make build-vs-buy decisions across OSS and SaaS AI technologies, set technical vision and roadmap, and recruit, mentor, and retain engineering talent.