onsite
Research Engineer - Generative AI Post Training & Agentic AI - Fraunhofer-Gesellschaft e.V. Zentrale Munchen
Research Engineer
Lead research on generative AI, focusing on post‑training optimization and agentic AI systems. Drive model refinement, policy learning, and deployment strategies using Python, PyTorch, and advanced ML techniques.
About the role
Key Responsibilities
- Design and implement post‑training methods to enhance generative models’ performance and safety.
- Develop agentic AI frameworks that enable autonomous decision‑making within complex environments.
- Collaborate with cross‑disciplinary teams to integrate reinforcement learning and policy optimization.
- Conduct rigorous experimentation, benchmark results, and publish findings in top venues.
- Translate research insights into scalable, production‑ready solutions.
Requirements
- Ph.D. or Master’s in Computer Science, AI, or related field with strong research background.
- Proven experience in generative modeling, post‑training techniques, and agentic AI.
- Proficiency in Python and deep learning frameworks such as PyTorch.
- Solid understanding of reinforcement learning, policy gradients, and safety‑critical AI.
- Excellent communication skills and ability to publish high‑impact research.
Skills
pythonmachine learninggenerative aireinforcement learningpytorch