Top AI & Machine Learning Jobs

Owns the enterprise strategy, roadmap, governance, service delivery, and adoption of Microsoft Copilot Studio and agent capabilities. Evaluates AI features, licensing, costs, security, compliance, and operational readiness; establishes governance and operating models; develops enablement, training, documentation, monitoring, and administration processes; and leads cross-functional initiatives supporting scalable enterprise AI adoption.

Leads responsible AI and automation adoption in local government by identifying operational improvements, evaluating tools, configuring workflows, managing pilots, training staff, and supporting sustained implementation. Coordinates custom development requirements, user testing, privacy and security reviews, data quality, ongoing ownership, and performance tracking. Collaborates with departments, IT staff, developers, leadership, and partner governments to improve services while managing risks and adoption barriers.

Develop and support AI-powered applications and automation solutions using Python, React JS, REST APIs, and enterprise integrations. Create and optimize prompts for LLMs, build user interfaces, integrate AI services, and participate in testing, troubleshooting, and application support. Collaborate with business and technology teams to deliver generative AI solutions. The role is intended for recent graduates with foundational AI, software development, and prompt engineering knowledge.

Leads an eight-person engineering team building AI agents, conversational analytics, data intelligence, voice agents, and their shared context graph and data platform. Owns technical strategy, architecture, delivery, hiring, reliability, security, tenant isolation, evaluation systems, and agent safety. The role remains hands-on, involving prototyping, coding, debugging, architecture reviews, production monitoring, and continuous improvement. Partners with product, design, customers, and forward-deployed engineering to turn freight-industry needs into scalable AI platform capabilities.

Develop predictive pressure-load models for external hypersonic aerodynamics under a DARPA project. Responsibilities include data-informed model development, testing, deployment, scientific publication, conference presentations, collaborator meetings, quarterly reporting, and mentoring junior researchers. The role requires machine learning, Python, end-to-end training, and high-speed aerodynamics expertise, with preferred experience in multiphysics modeling, explainable ML, physics-based loss functions, surface pressure models, and panel methods.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering judgment, reasoning quality, usefulness, correctness, and user guidance. Provide clear written feedback, distinguish response-quality levels, help define evaluation standards, and record brief video explanations. This flexible remote contract requires strong software engineering experience, familiarity with AI-assisted development workflows, and excellent English communication.

Lead product analytics and data science for a member platform, shaping product strategy through behavioral analysis, experimentation, segmentation, retention and churn modeling. Own product metrics end to end, build trusted datasets using Fivetran, dbt and BigQuery, and implement testing, monitoring, lineage and documentation. Partner cross-functionally with product, engineering, finance, operations and go-to-market teams to identify growth opportunities and support roadmap decisions.

Conduct fundamental AI safety research on reward-seeking, evaluation awareness, scheming, and misaligned preferences. Design and train model organisms, study reinforcement-learning dynamics, develop scalable evaluations, investigate frontier-model cognition, and establish scaling laws for scheming risks. Collaborate with leading AI labs and communicate findings through scientific writing and other media. The role requires empirical research ability, RL-trained LLM experience, strong quantitative analysis, conceptual creativity, and intensive engagement with AI progress.

Builds and enables responsible AI solutions across the organization. Responsibilities include managing AI use-case intake, coaching teams, developing Copilot Studio agents and Power Platform automations, supporting AI-powered developer tools, establishing governance and repeatable patterns, measuring adoption, and delivering training. The role requires strong communication, software development or architecture experience, Microsoft Copilot Studio expertise, and Microsoft 365 administration experience.

Support the design, development, testing, and deployment of AI-powered applications across front-end, back-end, and data workflows. Collaborate with engineers, researchers, product managers, and operators to translate customer needs into product requirements, integrate AI models, evaluate outputs, improve reliability and usability, and ship production-grade tools for government, healthcare, and industrial customers.