Hybrid Senior AI Researcher – Reinforcement Learning

at Aleph Alpha

• Job title: Senior AI Researcher – Reinforcement Learning
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: Node.js, Python
• Location requirements: Hybrid, Heidelberg, Germany

About the role

• Senior AI Researcher at Aleph Alpha advancing reinforcement learning techniques while leading large-scale experiments in hybrid work environment.

Responsibilities

• Conduct large-scale LLM training runs, analyze evaluation scores in depth, propose hypotheses for improvement and directly implement them in order to maximize performance on our benchmarks.
• Stay at the bleeding edge of RL research. You will identify, implement, and iterate on novel approaches to multi-turn reinforcement learning.
• Identify bottlenecks in our training setup and optimize our RL training loops for large-scale training.
• Partner with our other post-training teams to turn raw feedback into actionable training signals, ensuring that our RL iterations lead to measurable improvements in downstream performance.

Requirements

• A deep understanding of Reinforcement Learning theory and how it relates to modern RL methods.
• Experience with multi-node LLM training (ideally using RL). You understand how to scale multi-node RL trainings and can reason about and implement distributed algorithms.
• Familiarity with statistical methods for evaluation and experiment design.
• Ability to reason about what an evaluation/environment measures and whether it matters - not just run benchmarks, but understand them.
• Strong Python skills and comfort with ML tooling (especially torch distributed)
• Willingness to relocate to Heidelberg or travel regularly (potentially weekly).
• PhD in reinforcement learning or equivalent research experience.
• A history of contributions to top-tier venues (NeurIPS, ICML, ICLR, etc.) specifically regarding RL.
• Experience evaluating LLM models and crafting environments for training.

Benefits

• 30 days of paid vacation
• Access to a variety of fitness & wellness offerings via Wellhub
• Mental health support through nilo.health
• Substantially subsidized company pension plan for your future security
• Subsidized Germany-wide transportation ticket
• Budget for additional technical equipment
• Flexible working hours for better work-life balance and hybrid working model
• Virtual Stock Option Plan
• JobRad® Bike Lease