Research Engineer

Clera; Zürich; Vor Ort; CHF 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Equity

Visa sponsorship

Zusammenfassung

Clera is seeking a Research Engineer to turn experimental code into production-ready systems within an AI research team. You will build shared infrastructure and post-training pipelines to scale research while preserving experimental integrity.

You will collaborate with researchers to translate ideas into robust, maintainable software, focusing on data generation, training, evaluation pipelines, and efficient distributed infrastructure. Equity and visa sponsorship are provided.

Qualifikationen

• Proficient in Python and ML frameworks; able to translate research ideas into reliable software.
• Experience building model training, inference, or large-scale data processing pipelines.
• Understanding of ML experiments and how data, precision, and implementation affect results.
• Solid software engineering practices: testing, version control, and documentation.
• Experience with distributed training or data processing tools (e.g., PyTorch Distributed, DeepSpeed, Ray).

Aufgaben

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

Kenntnisse

Python

PyTorch

JAX

Distributed training

Testing

Version control

Documentation

Tools

PyTorch Distributed

DeepSpeed

Ray

Jobbeschreibung

About the Role

Join an AI research team as a Research Engineer, turning experimental code into production-ready systems. You will build the shared infrastructure and post-training pipelines that help research projects scale while preserving experimental integrity.

What You'll Do

• Turn research prototypes into tested, reusable data generation, training, and evaluation pipelines.

• Build distributed experiment infrastructure 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 ensuring changes preserve research results.

• Work with researchers to translate ideas into robust, maintainable software.

What We're Looking For

• 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 large-scale data processing.

• Understanding of machine learning experiments and how data, numerical precision, and implementation choices affect results.

• Sound software engineering practices, including testing, profiling, version control, and documentation.

• Distributed training or data processing experience with tools such as PyTorch distributed, DeepSpeed, or Ray is valuable.

• Familiarity with model-serving, machine learning, or experiment tracking tools is a plus; reinforcement learning systems and multimodal datasets are also useful.

Compensation & Benefits

Equity is provided. Visa sponsorship is available.

Location

On-site in Zurich, Switzerland. San Francisco, California is also listed as a work location.