Research Engineer, Mid-to-Senior

Clera; Zürich; On-site; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Health, dental, and vision coverage

Professional development support

Visa sponsorship

Relocation assistance

Job summary

Clera in Zürich, Switzerland, seeks an experienced AI software engineer to turn experimental code into reliable, production-ready systems. You will design and build post-training pipelines for generating, processing, and evaluating research data to scale experiments.

You will collaborate with researchers to translate ideas into robust, maintainable software, optimize GPU utilization, profiling, and data throughput, and contribute to testing and experiment tracking to preserve result integrity.

Qualifications

• 2 to 10+ years of experience building ML training, inference, or data pipelines in Python.
• Strong Python skills and hands-on experience with PyTorch, JAX, or similar frameworks.
• Experience in building and debugging software for model training, inference, or data processing at scale.
• Understanding of ML experiments and how data, precision, and implementation affect results.
• Sound software engineering practices: testing, profiling, version control, and documentation.
• Experience with distributed tools (PyTorch distributed, DeepSpeed, Ray) is helpful.

Responsibilities

• 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 experimental results.
• Collaborate with researchers to turn ideas into robust, maintainable software.

Skills

Python programming

Machine learning pipelines

Tools

PyTorch

JAX

Transformers libraries

DeepSpeed

Ray

vLLM

Experiment tracking tools

Job description

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.