Top AI Research Jobs in Chicago, IL

Evaluate and improve clinical AI systems through grading-criteria development, dialogue evaluation, clinical reasoning annotation, output review, guideline authoring, and difficult-case writing. The role requires physicians to assess accuracy, safety, completeness, clinical reasoning, and escalation guidance without providing direct patient care. Work is assigned across shared clinical AI workstreams and requires at least 20 hours weekly.

Partner with AI labs and enterprise teams on evaluation and human-data projects. Design methodologies, rubrics, data-collection approaches, quality frameworks, verifiers, validation systems, and reinforcement learning environments. Own projects from scoping through delivery, prototype tooling, advise customers, identify platform opportunities, collaborate with Product and Engineering, contribute to research publications, mentor colleagues, and communicate advanced AI concepts to diverse stakeholders.

Define clinical reasoning, safety boundaries, evaluation scenarios, datasets, rubrics, and acceptance thresholds for AI-enabled chronic disease products. Analyze failures and edge cases, support clinical validation and outcomes research, interpret clinical and EHR data, and collaborate with Product, Engineering, AI/ML, Data, informatics teams, and clinical stakeholders on integrations and workflows.

SynX Therapeutics, a biotech start-up, invites speculative applications for future roles related to drug discovery and engineered biology.

Conduct hands-on research with frontier AI labs to evaluate model behavior, identify failure modes, and design interventions that improve reliability. Responsibilities include designing evaluations, building data pipelines and fine-tuning workflows, collaborating with internal and external stakeholders, and addressing challenges involving long-context reasoning, tool use, and real-time feedback loops.

Conduct open-ended AI research focused on end-to-end training workflows using LanceDB. Design replicable experiments and benchmarks, demonstrate workflows across AI domains, develop content, publish research and models, and collaborate with engineering and product teams. The role requires deep learning expertise, experience training state-of-the-art models, open-source software development, strong prioritization, product awareness, and staying current with AI research.

Conduct AI and machine learning research focused on physics-driven modeling, simulation, reinforcement learning, multi-agent systems, and hybrid models. Develop and integrate novel algorithms into prototypes and production AI systems. Collaborate with research, engineering, and product teams, contribute to technical publications and patent disclosures, and support mission-critical modeling and decision-support solutions for space operations.

Conduct original research on reliable agentic AI, developing methods for simulation, evaluation, optimization, regression control, and continuous learning. Analyze agent failures, traces, and human feedback; create experiments and prototypes; and translate research into production-facing systems. Collaborate with product and engineering teams, contribute to technical strategy, and provide rigorous experimental evidence. The role requires strong research depth, publication or open-source contributions, hands-on Python development, and expertise in LLM agents or agentic systems.

Oversee global analytics and algorithm design initiatives for a nonprofit: identify high-impact projects, coordinate with student directors, collect feedback, design and run training for developers and technical advisors, and form partnerships to support implementation. Volunteer commitment ~5-6 hours/week.

Annotates data accurately according to project guidelines, performs quality checks, provides feedback on annotation tools and processes, collaborates with project teams, maintains efficiency, and reports issues for resolution.