Top AI & Machine Learning Jobs in Boston, MA

Lead design, development, deployment, and support of foundation model training and LLM inference platforms. Build similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, and scalability; contribute to technical vision and roadmap while partnering across engineering, research, product, and program teams.

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

Lead and grow an AI engineering team to design, build, deploy, and support production-scale generative AI systems. Oversee foundation model training, LLM inference, vector search, guardrails, evaluation, governance, and observability. Make build-vs-buy decisions across open source and SaaS, optimize LLM performance for cost/latency/throughput, set technical vision and roadmap, and attract/mentor top AI engineering talent.

Lead an AI engineering team to design, build, deploy, and optimize large-scale generative AI systems. Oversee foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and make strategic build-vs-buy decisions. Drive technical vision, roadmap, and talent development while ensuring scalable, cost-efficient, and responsible AI production systems.

Lead design, develop, deploy, and support foundational AI systems (LLM training/inference, similarity search, guardrails, observability). Partner cross-functionally to optimize scalability, cost, latency, and throughput, apply state-of-the-art research to production, and shape long-term AI platform roadmap.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

The role involves designing and developing AI software solutions, collaborating with cross-functional teams, and optimizing large-scale AI systems for performance and scalability.

The Senior Lead AI Engineer will develop and support AI software components, partner with cross-functional teams, and enhance AI systems performance. Responsibilities include designing, deploying, and optimizing AI models for improved banking services.

Lead the development of AI-powered products by collaborating with cross-functional teams, designing AI components, and optimizing models for performance and scalability.

The Distinguished Applied Researcher will drive AI-powered product innovations, guide teams, and conduct impactful applied research while collaborating cross-functionally.