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

• Subsidized Germany-wide transportation ticket

Education Requirements:

• PhD in machine learning, NLP, statistics, or a related field (valued but not required)

Experience Requirements:

• Experience with LLM evaluation, benchmark design, evaluation dataset curation, and experimental design

• Familiarity with statistical methods for evaluation and experiment design

• Track record of shipping impactful technical work (research or infrastructure)

• Strong Python skills and comfort with ML tooling (PyTorch, evaluation frameworks, distributed systems)

• Ability to reason about what an evaluation measures and whether it matters

Other Requirements:

• Ownership mentality

• Willingness to relocate to Heidelberg or travel regularly (potentially weekly)

• Understanding of foundation model training (preferred)

• German language proficiency (preferred)

Responsibilities:

• Own benchmarks end-to-end: Select, implement, and maintain the evaluation suite used during pre-training

• Build evaluation infrastructure: Develop and optimise the pipelines that run evaluations against training checkpoints

• Design aggregation and reporting: Define how benchmark results translate into training decisions

• Close capability gaps: Identify where models fall short and create benchmarks that measure progress

• Own German evaluation: Ensure rigorous assessment of German language capabilities

Benefits:

• 30 days of paid vacation

• Access to a variety of fitness & wellness offerings via Wellhub

• Mental health support through nilo.health

• JobRad® Bike Lease

• Substantially subsidized company pension plan

Experience Requirements:

• Extensive experience in strategy, management consulting, or serving as a Chief of Staff / Operations leader

• Strong understanding of both AI research and product development environments

• Proven track record of driving complex, cross-functional projects and influencing at multiple levels

• Experience in high-growth environments, startups, or deep-tech companies is highly desirable

• Excellent organizational, analytical, and communication skills

Other Requirements:

• Fluency in English required; fluency in German is a strong plus

• Comfort navigating ambiguity and balancing strategic vision with hands-on execution

Responsibilities:

• Strategic and Operative Support to the CRO: Work on daily priorities, communication, and strategic initiatives

• Shape Organizational Performance and Scalability: Design structures and processes to enable growth

• Drive Cross-Functional Collaboration: Ensure smooth coordination between research, engineering, and product

• Enable Leadership Effectiveness: Anticipate roadblocks and structure problem-solving

• Support Data-Driven Decision-Making: Synthesize technical and operational data into clear narratives

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

• Subsidized Germany-wide transportation ticket

Education Requirements:

• PhD in reinforcement learning or equivalent research experience (preferred)

Experience 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)

• Familiarity with statistical methods for evaluation and experiment design

• Strong Python skills and comfort with ML tooling (especially torch distributed)

• Ability to reason about what an evaluation/environment measures and whether it matters

Other Requirements:

• Willingness to relocate to Heidelberg or travel regularly (potentially weekly)

• History of contributions to top-tier venues like NeurIPS, ICML, ICLR (preferred)

• Experience crafting environments for training (preferred)

Responsibilities:

• Hill-climb in large-scale training: Conduct training runs, analyze scores, and implement improvements

• Theoretical innovation: Stay at the bleeding edge of RL research and iterate on novel approaches

• Scale our training infrastructure: Identify bottlenecks and optimize RL training loops

• Cross-functional collaboration: Partner with post-training teams to turn feedback into actionable signals

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

• Subsidized Germany-wide transportation ticket

Experience Requirements:

• Proficient in Python and the PyTorch library

• Strong engineering background in parallel and/or distributed systems

• Hands-on experience with modern machine learning techniques (especially LLMs)

• Deep understanding of the CUDA programming model

• Experience in distributed programming with APIs like NCCL or MPI

Other Requirements:

• Regular on-site collaboration in Heidelberg is required

• Experience analyzing profiling traces with tools such as PyTorch Profiler and Nvidia Nsight

• Contributions to modern distributed training frameworks like TorchTitan or Megatron-LM (preferred)

• Proven track record working on the NVIDIA Blackwell architecture (preferred)

Responsibilities:

• End-to-End Optimization: Profile training loops to identify system- and kernel-level bottlenecks

• Distributed Strategy and Topology: Configure and tune composite parallelism strategies (TP, DP, FSDP, etc.)

• Hardware-Aware Modeling: Partner with Researchers to define architectures for hardware efficiency

Benefits:

• Open communication

• Flat hierarchies

• Flexible working models

• Hybrid work model

• Potential for long-term relationship

Education Requirements:

• Student of natural sciences, mathematics, or computer science

• Excellent academic record

• Recent transcript of records

Experience Requirements:

• Knowledge of Python

• Basic computer science algorithms and data structures

• Software engineering principles

• Strong English-language communication skills

Other Requirements:

• Life-long curiosity-driven learner

• Growth mindset and commitment to excellence

• Ability to work in Germany (legally and logistically)

• Duration: 3–6 months

Responsibilities:

• Leverage Python scientific stack, TypeScript or C++

• Developing and/or testing novel deep learning models

• Building user-facing products and features

• Applying models to clients’ research questions