Senior Machine Learning Research Developer

European Tech Recruit; Berlin; Hybrid; EUR 90,000 - 150,000; Full time

Job summary

European Tech Recruit is partnering with an AI company in Berlin to hire a Senior Machine Learning Research Developer on a hybrid basis. You will work closely with ML researchers and engineers to tackle training and inference challenges on large-scale models, translating research concepts into robust implementations.

You will also help design workflows and build infrastructure to run complex experiments in high-performance computing environments, ensuring scalable and reproducible ML development.

Qualifications

• MSc or higher in ML, CS or related field.
• 5+ years of industry experience in ML workflows.
• Hands-on with HPC environments and large-scale ML workloads.
• Experience with PyTorch, TensorFlow or JAX.
• Experience with cloud platforms such as AWS, GCP or Azure.
• Familiarity with Docker and Kubernetes.
• Familiarity with vector databases.
• Strong software engineering practices and well-documented code.
• Understanding of distributed computing and high-performance ML workloads.

Responsibilities

• Collaborate with ML researchers to accelerate training and inference.
• Facilitate efficient implementation of ML models, architectures and simulated environments.
• Design and implement workflows for research experiments from small-scale to large projects.
• Develop tools, libraries, and infrastructure to optimise computing resources.
• Improve efficiency, scalability and reproducibility of ML workflows.
• Translate research concepts into reliable, production-quality implementations.
• Establish and maintain best practices for ML model development and experimentation.
• Identify bottlenecks across training and inference workflows and develop solutions.
• Collaborate across research, engineering and infrastructure teams.

Skills

Collaboration

High-performance computing

Problem solving

Education

MSc or higher in ML/CS

Tools

PyTorch

TensorFlow

JAX

AWS

GCP

Azure

Docker

Kubernetes

Vector databases

Distributed computing

Job description

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.

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