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Senior Machine Learning Research Engineer
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1 month ago
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Important information
Contract type:
Permanent
Location:
Berlin, Germany
Work mode:
Onsite
Published on:
17 October 2026
What they need
Our client is a non-profit organisation advancing research and technical solutions for safe-by-design AI systems. They are seeking a Senior Machine Learning Research Developer to join a highly technical team working at the forefront of ML research and development.
You will work closely with ML researchers and engineers to solve challenging training and inference problems involving large-scale models. You will translate research concepts into robust implementations, build infrastructure for complex experiments and optimise workflows for high-performance computing environments.
This role sits at the intersection of machine learning research, software engineering and high-performance computing, with direct impact on the development and evaluation of advanced AI systems.
Key Responsibilities
- Partner with ML researchers to accelerate research, model training and inference.
- Implement novel ML models, architectures and simulated environments.
- Design workflows for experiments ranging from small-scale research to large-scale projects.
- Develop tools, libraries and infrastructure to optimise compute resources.
- Improve the efficiency, scalability and reproducibility of ML workflows.
- Translate research concepts into reliable, production-quality implementations.
- Establish and maintain best practices for model development and experimentation.
- Identify training and inference bottlenecks and develop solutions.
- Collaborate across research, engineering and infrastructure teams.
Requirements
- Degree in Computer Science, Computer Engineering, Software Engineering or a related field.
- MSc or higher in ML, Computer Science or a related discipline, or equivalent professional experience.
- 5+ years' industry experience designing and implementing complex ML workflows.
- Strong hands-on experience with HPC environments and large-scale ML workloads.
- Extensive experience with ML frameworks such as PyTorch, TensorFlow or JAX.
- Experience contributing to high-quality deep learning rese
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