Senior Machine Learning Research Developer

European Tech Recruit are working closely with an exciting AI company committed to advancing research and creating technical solutions that enable safe-by-design AI systems.

They are looking for a talented Senior Machine Learning Research Developer to join them on a hybrid basis in Berlin.

In this role, you will work closely with ML research scientists and engineers to solve challenging training and inference problems involving large-scale models. You will help translate research concepts into robust implementations, develop the infrastructure required to run complex experiments and optimise workflows for high-performance computing environments.

Responsibilities as Senior Machine Learning Research Developer:

• Collaborate closely with ML researchers to accelerate research, model training and inference.
• Facilitate the efficient implementation of novel machine learning models, architectures and simulated environments.
• Design and implement workflows for research experiments, ranging from small-scale experimental scenarios to large-scale projects.
• Develop tools, libraries and infrastructure to optimise the use of computing resources.
• Improve the efficiency, scalability and reproducibility of machine learning development workflows.
• Help translate research concepts and experimental ideas into reliable, production-quality implementations.
• Establish, document and maintain best practices for machine learning model development and experimentation.
• Identify technical bottlenecks across training and inference workflows and develop solutions to address them.
• Collaborate across research, engineering and infrastructure teams to support evolving technical requirements.

Requirements:

• Advanced degree (MSc or higher) in Machine Learning, Computer Science or a related field, or equivalent professional experience.
• 5+ years of industry experience designing and implementing complex machine learning workflows.
• Strong hands-on experience working with high-performance computing environments and large-scale machine learning workloads.
• Extensive experience with one or more major ML frameworks, such as PyTorch, TensorFlow or JAX.
• Demonstrated experience contributing to high-quality research projects in deep learning.
• Experience working with large-scale model training and/or inference.
• Experience working with cloud platforms such as AWS, GCP or Azure.
• Familiarity with containerisation technologies such as Docker and Kubernetes.
• Familiarity with modern data infrastructure and platforms, including technologies such as vector databases.
• Strong software engineering practices, including writing maintainable, well-tested and documented code.
• Understanding of distributed computing and high-performance ML workloads.