Top AI & Machine Learning Jobs

Research and prototype next-generation Vision-Language-Action architectures for autonomous driving. Develop multimodal foundation models, world models, predictive simulations, long-horizon planning systems, and agentic driving architectures integrating reasoning, memory, planning, and action. Train and fine-tune large-scale models, implement current AI research, build data pipelines, and contribute research prototypes to production systems in collaboration with distributed global teams.

Design and build full-stack, AI-powered developer platform capabilities. Implement backend JVM/Spring services and frontend React interfaces, integrate LLMs/agentic tooling, own service lifecycle (deployments, incidents, reliability), uphold API governance, write documentation, and collaborate across product and engineering teams.

Lead end-to-end model lifecycle as infrastructure: standardized packaging, model CI/CD, serving with versioned contracts, automated deployment/rollback, monitoring and drift detection. Extend platform discipline to LLM/VLM/agentic workloads (prompt/versioning, generative evaluation, guardrails, token cost/latency observability). Define API boundaries, enable self-serve safe deployments, own operational seams (vector stores, tracing), and mentor engineers to grow the ML/LLM ops function.

Lead insurance AI transformation engagements by mapping and redesigning workflows, capturing expert knowledge, prioritizing use cases, facilitating client workshops, shaping proposals, and co-designing AI solutions. Partner with business leaders, domain experts, AI engineers, and technology teams to define requirements, evaluation methods, governance, adoption plans, and implementation pathways for generative AI and agentic systems.

Lead AI enablement and change management across the firm’s East Coast offices. Design and deliver attorney-focused training, AI academies, workshops, adoption campaigns, and communications for legal technology tools. Build stakeholder relationships, support responsible AI adoption, analyze usage data, report regional progress, address implementation barriers, and collaborate with legal technology, training, professional development, and practice group teams. The role requires autonomous regional leadership, one-to-one and group facilitation, and travel to regional and potentially international offices.

Design and research agentic AI and reinforcement learning systems: build auto-research and coding agents, develop recursive self-improvement and multi-agent frameworks, run RL experiments (RLHF, DPO, PPO), curate training data pipelines, and publish results at top ML venues.

Build and deploy AI agents, automated workflows, integrations, analytics solutions, and internal tools across an advertising agency, initially focused on media operations. Partner with teams to identify opportunities, improve processes, ensure data reliability and governance, test solutions with users, drive adoption, and scale successful AI-enabled workflows. Evaluate emerging AI technologies and translate business needs into practical, measurable solutions.

Design, develop, deploy, and support scalable AI applications, automation solutions, digital agents, and generative AI platforms. Lead agentic workflow development using AWS, OpenAI, Bedrock, SageMaker, LangChain, Kubernetes, and Docker. Support the full AI lifecycle, platform reliability, monitoring, security, governance, and continuous improvement. Lead technical workstreams, collaborate with business and technology teams, and mentor less experienced engineers.

Own strategy and delivery of AI-driven products across customer and internal use cases. Lead discovery, write requirements, partner with engineers, design experiments/A-B tests, monitor performance, and champion responsible AI practices.

Lead architecture, development, and deployment of large-scale, production AI systems (LLMs/agentic systems). Define enterprise AI architecture, modernize legacy systems, implement AI-enabled SDLC and DevOps practices, establish governance and responsible AI, and provide technical leadership and mentorship across engineering teams.