Research Engineer, Mid-to-Senior

About the Role

Join an AI research team to turn experimental code into reliable, production-ready systems. You will build post-training pipelines for generating, processing, and evaluating research data, helping research ideas scale into repeatable experiments.

What You'll Do

• Convert research prototypes into tested, reusable data generation, training, and evaluation pipelines.
• Build distributed experiment support for data loading, checkpointing, and collecting agent interactions.
• Profile workloads and improve GPU utilization, memory efficiency, and data throughput.
• Develop tests, experiment tracking, and debugging tools while preserving the integrity of experimental results.
• Collaborate with researchers to turn ideas into robust, maintainable software.

What We're Looking For

• Typically 2 to 10 or more years of relevant experience building machine learning training, inference, or data pipelines in Python.
• Strong Python skills and hands-on experience with PyTorch, JAX, or a comparable machine learning framework.
• Experience building and debugging software for model training, inference, or data processing at scale.
• Understanding of machine learning experiments, including how data, numerical precision, and implementation choices affect results.
• Sound software engineering practices, including testing, profiling, version control, and documentation.
• Experience with distributed tools such as PyTorch distributed, DeepSpeed, or Ray is helpful, as is familiarity with Transformers libraries, vLLM, or experiment tracking tools.
• Background in reinforcement learning systems or working with video, audio, or image datasets is a plus.

Compensation & Benefits

Competitive compensation with equity is offered, along with health, dental, and vision coverage and professional development support. Visa sponsorship and relocation support are available.

Location

This is a full-time, on-site role in Zürich, Switzerland.