ML Engineer, Agents & Reasoning
Core
Build agentic AI systems that reason, plan, and act inside real materials discovery workflows, handling messy reality like failed experiments and contradictory data.
Role type
Senior IC machine-learning engineer (agentic systems & reasoning)
Builds
Agentic decision-making systems for scientific discovery, connecting predictive models to real experimental and simulation systems
Domain
Materials science + AI agents & control systems
Deliverable
production ML models
Required skills
agentic system design, planning & control logic, probabilistic reasoning, uncertainty-aware decision-making, modern ML frameworks (PyTorch, JAX), software engineering, system observability
Preferred skills
scientific data modeling, optimization, working with lab automation teams
Technologies
PyTorch, JAX (via careerplan.io/jobs/2521701-ml-engineer-agents-reasoning-at-dunia-innovations-gmbh)
Responsibilities
Design and implement agentic systems that plan, reason, and act across discovery workflows; Implement planning, control logic, and uncertainty-aware decision-making tailored to physical systems; Collaborate with researchers to embed predictive models into agent workflows; Build evaluation frameworks for decision quality and system behavior; Translate research concepts into robust, maintainable ML systems
Seniority
Mid-Senior, hands-on IC
