Top AI & Machine Learning Jobs

Design, develop, test, deploy, and operate AI-driven software and scalable infrastructure. Build APIs and third-party integrations, architect production systems, research emerging technologies, and provide technical leadership and mentorship. The role requires independent execution, collaboration with cross-functional teams, and work on mission-critical defense and intelligence applications.

Designs and delivers GenAI training focused on workflow integration, use-case identification, responsible use, and tool adoption. Conducts needs analyses, develops curricula and job aids, collaborates on change management, measures learning outcomes, and continuously improves content. Delivers frequent virtual training sessions using communication platforms, coordinates with partners, reports learner feedback, supports internal tools, and may travel for onsite instruction.

Lead data science projects from ideation through enterprise impact, building scalable and well-tested solutions that improve healthcare outcomes. Apply probability, statistics, machine learning, SQL, and Python to develop data-driven products and insights. Partner with stakeholders, assess product performance, identify strategic improvements, mitigate risks, and mentor teammates while aligning initiatives with business objectives.

Conduct externally funded artificial intelligence research, publish scholarly work, teach undergraduate and graduate courses, mentor students, develop AI curriculum, and contribute to departmental, university, and professional service.

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

Lead development of customized AI solutions for manufacturing clients. Analyze manufacturing data, build predictive models and tools, identify product opportunities, collaborate with customers and internal teams, and present data-driven findings to technical and non-technical stakeholders.

Build and improve AI agent systems focused on Model Context Protocol and memory. Work includes developing MCP servers and clients, integrating tools and memory into agent loops, experimenting with context retrieval, testing behavior, documenting implementations, and shipping iterative improvements. The role emphasizes Python development, curiosity about agent systems, clear communication, collaboration, and learning through hands-on experimentation.

Develops end-to-end computer vision and perception software for unmanned aircraft, including target detection, classification, tracking, aimpoint selection, EO/IR imagery, and embedded deployment. Owns accuracy-latency tradeoffs, evaluation against flight data, sensor integration, regression testing, and perception interfaces. Provides senior technical design and code review while supporting mission-critical target discrimination and operator-authorized engagement workflows.

Develop algorithms and end-to-end modeling pipelines that transform multimodal plasma and process sensor data into material fingerprints, metrics, and alerts. Design automated experiments integrating plasma hardware, robotics, sensing, and data capture. Validate and monitor models, detect data artifacts and drift, and support deployment across edge, host, and cloud systems. Collaborate with engineering teams and communicate results to technical and nontechnical stakeholders in laboratory and industrial environments.

Develops post-training recipes and data pipelines for AI models, creates evaluations, builds agentic systems with custom tools, and integrates reasoning capabilities into live scientific workflows. The role collaborates with scientists, robotics engineers, and operations teams to improve experimental design and assay development while shaping the technical direction of a new machine learning team.