Senior ML Research Developer

European Tech Recruit; Berlin; Hybrid; EUR 85.000 - 125.000; Vollzeit

Zusammenfassung

European Tech Recruit in Berlin offers a Senior Machine Learning Research Developer role in a hybrid setup. You will translate research ideas into robust implementations, build experimental workflows, and optimise HPC-based pipelines for large models.

Join a technically driven team focused on scalable ML research, with collaboration across researchers and engineers to push state-of-the-art training and inference.

Qualifikationen

• Degree in CS/CE/SE or related; Master’s preferred.
• 5+ years designing and implementing complex ML workflows.
• Strong hands-on HPC and large-scale ML workloads.
• Experience with major ML frameworks and cloud platforms.

Aufgaben

• Collaborate with ML researchers to translate research concepts into production-quality implementations.
• Facilitate efficient implementation of novel ML models, architectures, and simulated environments.
• Design experimental workflows from small-scale to large-scale projects.
• Develop tools and infrastructure to optimise computing resources and reproducibility.

Kenntnisse

ML Research

HPC

Software Engineering

Technical Communication

Ausbildung

Master's or higher in CS/CE/SE

Tools

PyTorch

TensorFlow

JAX

Docker

Kubernetes

AWS

GCP

Azure

Vector databases

Jobbeschreibung

Senior ML Research Developer - AI Safety Research Non-Profit - Berlin (Hybrid)

We are seeking a Senior Machine Learning Research Developer to join a highly technical team working at the forefront of machine learning research and development. 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.

Research Acceleration & Implementation:

• Collaborate closely with ML researchers to translate complex research concepts and experimental ideas into reliable, production-quality implementations.
• Facilitate the efficient implementation of novel ML models, architectures, and simulated environments.

Workflow & Infrastructure Optimization:

• Design and implement experimental workflows ranging from small-scale scenarios to large-scale projects.
• Develop tools, libraries, and infrastructure to optimise computing resources and improve reproducibility and scalability.

Technical Leadership & Collaboration:

• Identify technical bottlenecks across training and inference workflows and build solutions.
• Establish, document, and maintain best practices for ML model development and cross-team technical collaboration.

Requirements:

• Degree in Computer Science, Computer Engineering, Software Engineering, or a related discipline (Master's or higher preferred).
• 5+ years of industry experience designing and implementing complex machine learning workflows.
• Strong hands-on experience with high-performance computing environments and large-scale ML workloads.
• Extensive proficiency with major ML frameworks (PyTorch, TensorFlow, JAX).
• Technical familiarity with cloud platforms (AWS, GCP, Azure), containerisation (Docker, Kubernetes), vector databases, and distributed computing.
• Strong software engineering practices and effective technical communication skills.