Top AI & Machine Learning Jobs

Lead presales engagements to uncover business drivers and design responsible, scalable AI solutions on the Microsoft cloud. Run enterprise discovery workshops, shape measurable outcomes, architect across Azure Data/AI/Security/Integration/Power Platform, produce SOWs and phased delivery plans, and communicate value to executive stakeholders while partnering with sales and delivery for deal readiness and risk mitigation.

Lead end-to-end post-training of open-weight language models on proprietary legal data, including dataset development, objective design, supervised fine-tuning, preference optimization, reinforcement learning, evaluation, and distributed training. Build production model-serving systems, agents, tooling, and infrastructure. Partner with product engineers, lawyers, and domain experts to translate workflows into model and evaluation strategies and deliver AI capabilities to users.

Build backend architecture and infrastructure for LLM-driven agent systems, including orchestration, tool integration, context management, evaluation, observability, and production deployment. Develop services connecting AI models with insurance data and platform APIs, define reliable AI-native architectural patterns, and collaborate with product, design, and engineering teams to deliver underwriting workflows.

Works with stakeholders to identify valuable business problems and direct AI-assisted development of internal applications, automations, agents, integrations, reporting, and data pipelines. Owns solutions through testing, documentation, deployment, onboarding, and support. Builds Claude capabilities using MCP servers, connectors, skills, and agent workflows. Provides employee enablement and coaching, follows AI governance standards, and measures adoption and business impact.

Build and maintain ML infrastructure for robot learning, including training pipelines, experiment tracking, model versioning, deployment, sensor-data processing, simulation, monitoring, and feedback systems. Develop internal tools for dataset exploration, testing, evaluation, and productionization. Partner with AI researchers and robotics engineers to deliver scalable software supporting AI models from data collection through deployment on robotic systems.

Optimize dataset quality and value through marketplace incentives, task targeting, bonuses, payouts, eligibility, and experimentation. Design treatment assignments and holdouts, evaluate incremental collection against objective functions, identify Goodhart effects, and translate findings into operational actions. Partner with software teams to ship incentive and payout changes into the collection product. Experience with marketplace experimentation, pricing, growth, real-money payouts, or product implementation is preferred.

Own AI quality for an agentic enterprise platform, including evaluation datasets, grading rubrics, regression testing, model benchmarking, cost optimization, observability, and feedback systems. Partner with engineering, product, design, sales, and client-facing teams to diagnose failures, improve prompts and models, define quality standards, and ship product changes. The role combines hands-on Python and SQL analysis with product management, LLM evaluation, RAG, document AI, and agent workflow expertise.

Develops statistical, machine learning, predictive, and advanced analytical solutions using structured and unstructured public health data. Integrates and analyzes data from surveillance, research, and administrative sources; evaluates data quality; creates visualizations and reports; monitors analytical tools; and translates findings into actionable public health insights. Collaborates with multidisciplinary CDC program teams and communicates technical results to technical and non-technical audiences.

Design and evaluate AI-enhanced instructional materials and learning experiences, lead Agentic AI implementations, collaborate with academic and technical teams, assess educational effectiveness, and train faculty and staff on AI-enabled teaching practices. The role requires instructional design expertise, higher education experience, knowledge of ethical AI and data privacy, familiarity with adaptive learning and data analytics, and a portfolio or published work demonstrating AI in education.

Leads Mayo Clinic’s enterprise AI and robotics strategy, governance, portfolio prioritization, operational enablement, and workforce adoption. The role develops multi-year roadmaps, establishes responsible AI and interoperability standards, partners with clinical, technical, legal, facilities, and security stakeholders, and oversees procurement and vendor governance. As a people leader, the Director manages operations managers, execution processes, reporting, budgets, and cross-functional initiatives while advising senior executives on AI strategy and value realization.