Top AI & Machine Learning Jobs

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.

Design, train, and interpret foundation models for multimodal real-world sensor data. Develop representation learning, multimodal alignment, self-supervised learning, and model adaptation methods. Diagnose limitations, conduct experiments, collaborate with engineering and product teams to productionize research, and publish findings at leading machine learning and sensing conferences.

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.

Leads architecture for scalable, reliable agent-based AI products. Partners with product, engineering, data science, clinical, and customer teams to translate needs into architectures, prototypes, technical recommendations, and delivery plans. Conducts technical discovery, engages early-stage customers, evaluates adoption barriers, and guides solutions from proof of concept to production. Requires strong architecture judgment, communication, and experience shipping large-scale AI systems, with healthcare, deep learning, or NLP experience preferred.

Leads the credit union’s enterprise AI and automation function, setting strategy, governance, operating models, roadmaps, and prioritization frameworks. Identifies and delivers AI, generative AI, RPA, and intelligent automation use cases while ensuring regulatory, risk, ethical, and data governance alignment. Partners with business and technology teams on solution selection, process improvement, adoption, training, vendor coordination, KPI tracking, and value realization. Builds and manages a high-performing team.