8 hours ago
Zürich, SwitzerlandMid Level
Responsibilities
- Turn research prototypes into tested, reusable data-generation, training, and evaluation pipelines.
- Build distributed experiment support for data loading, checkpointing, and collection of agent interactions.
- Profile workloads and improve GPU utilization, memory efficiency, and data throughput.
- Develop tests, experiment tracking, and debugging tools while preserving research-result integrity.
- Collaborate with researchers to translate ideas into maintainable software.
Requirements
- Experience building ML training, inference, or data pipelines in Python.
- Strong Python skills and hands-on experience with PyTorch, JAX, or comparable machine learning frameworks.
- Understanding of ML experiments, including the effects of data, numerical precision, and implementation choices on results.
- Sound software engineering practices involving testing, profiling, version control, and documentation.
- Distributed training or data-processing experience with PyTorch Distributed, DeepSpeed, or Ray is valuable.
- Familiarity with Hugging Face Transformers, vLLM, Weights & Biases, or MLflow is useful.
- Experience with reinforcement learning systems or multimodal datasets is a plus.
Benefits
- Competitive compensation and equity are offered.
- Visa sponsorship is available.
- The role is on-site in Zürich, Switzerland.