Top AI & Machine Learning Jobs

Lead the architecture, development, optimization, and operation of production LLM and AI automation systems. Design capabilities including agents, retrieval, code generation, tool use, model routing, evaluation, and observability. Drive platform modernization, scalability, reliability, architecture, and code quality while mentoring engineers and influencing technical practices across teams. Build prototypes, establish engineering standards, conduct reviews, and communicate complex technical concepts through documentation and cross-functional collaboration.

Develop and support AI/ML applications and infrastructure for a federal healthcare agency. Build CI pipelines, automate deployment and infrastructure processes, manage cloud and server environments, troubleshoot applications and networks, monitor performance, and implement security and data protection. Collaborate with architects, developers, DBAs, stakeholders, and Agile teams while conducting code reviews, documenting solutions, mentoring colleagues, and supporting AI/ML prototyping, evaluation, integration, and production deployment.

Customer-facing Cloud Solution Architect specializing in generative AI and Microsoft 365 Copilot. Advise, design, deploy, and govern AI-powered workplace and agentic solutions; lead adoption, change management, identity/security/compliance controls, and analytics-driven usage measurement. Coordinate partners and delivery teams, engage executives, and manage adoption/consumption milestones while capturing feedback to improve products and delivery.

Analyze business problems using SQL, Python or R, and statistical methods to identify trends, test hypotheses, and develop insights or recommendations. Visualize findings in Tableau and collaborate with data engineers to present results to stakeholders. The role requires clear communication, flexibility, and the ability to explain analytical approaches and adapt deliverables to business needs.

Own the equipment AI roadmap for a semiconductor fab and deploy AI/ML, advanced analytics, sensor, vision, controls, automation, and AMR solutions. Integrate equipment, MES, facilities, and manufacturing data into reusable datasets, digital twins, and data lakes. Develop maintenance knowledge assistants, predictive and diagnostic tools, and production dashboards. Lead projects from proof of concept through sustained deployment, coordinate with IT, engineering, vendors, and technicians, and mentor teams on data and AI practices.

Early-employee, open-call role for candidates passionate about accelerating UAV swarm and spatial AI capabilities for national security. Help shape company direction, propose a role, and describe relevant past projects. Requires optimistic, tenacious, self-determined, and highly motivated individuals. Must meet ITAR eligibility (US Citizen, Green Card holder, or asylee/refugee).

Design, build, and operate large-scale AI/HPC infrastructure spanning job scheduling (Beaker), runtimes, networking, and storage. Drive automation, performance optimization, root-cause analysis for distributed GPU workloads, mentor engineers, and collaborate with researchers to prioritize and deliver scalable orchestration and cluster health tooling.

Build and operate production-grade private AI platform capabilities, including agentic and multi-agent workflows, orchestration, evaluation, monitoring, fine-tuning, runtime optimization, safety controls, APIs, and rollback mechanisms. Partner with data and infrastructure teams to improve reliability, performance, and deployment quality. Senior engineers also mentor teammates, review designs, and lead major platform components.

Leads TireHub’s enterprise automation and AI enablement program, architecting and delivering solutions across Power Platform, Copilot Studio, and Microsoft Foundry. Manages and develops engineers, establishes technical standards, designs AI agents and RAG solutions, integrates enterprise systems, ensures security and observability, and partners with stakeholders to identify high-value automation opportunities. The role balances hands-on engineering with architecture, Agile delivery leadership, technical coaching, and cross-functional program execution.

Co-lead a new 10-week AI safety replication program: select replication targets, mentor fellows, take technical ownership of replications, set publication standards, represent the program externally, and support fundraising and long-term planning. Work includes experimental design, review, writing, and coordination with XLab operations.