Senior ML Research Scientist – Deep Learning / Frontier Models / PyTorch / JAX

European Tech Recruit; Berlin; Vor Ort; EUR 90.000 - 150.000; Vollzeit

Zusammenfassung

European Tech Recruit is partnering with a highly technical AI research organisation in Berlin to hire a Senior Machine Learning Research Scientist. The role focuses on designing, evaluating, and improving innovative ML models for complex research challenges, blending theory with practical algorithms.

You will work with researchers, mathematicians, and ML engineers to translate theoretical advances into production-ready workflows, develop rigorous experiments, and push frontier models to

Qualifikationen

• Advanced degree in Computer Science, Mathematics, Machine Learning, or related discipline.
• 5+ years of experience on deep learning research projects, especially involving large-scale or frontier models.
• Experience training, adapting, and/or fine-tuning large-scale ML models.
• Experience with transfer learning, domain adaptation, or meta-learning.
• Proven track record of contributing to high-quality ML or deep learning research.
• Strong experience with PyTorch, TensorFlow, or JAX.
• Experience developing, training, and evaluating ML models in distributed computing environments.
• Strong Python development skills for research and production.
• Experience in NLP.
• Experience with probabilistic graphical models or related statistical modelling techniques.
• Publications or demonstrable contributions to high-quality deep learning research.
• Experience with large-scale distributed training and inference infrastructure.

Aufgaben

• Propose, design, and implement novel machine learning models and methodologies for complex research problems
• Collaborate with mathematicians and specialist research scientists to translate theoretical developments into practical ML algorithms and models
• Adapt and fine-tune existing frontier models for specific applications, domains, and research scenarios
• Design and implement rigorous experimental protocols and evaluation frameworks
• Develop reproducible experiments capable of operating at the scale and complexity required for frontier models
• Analyse and interpret experimental results to identify new research directions and inform future hypotheses
• Benchmark and optimise model performance, efficiency, and resource utilisation

Kenntnisse

PyTorch

TensorFlow

JAX

Python

Distributed training

NLP

Transfer learning

Domain adaptation

Meta-learning

Ausbildung

PhD in CS/ML

Tools

MPI

Jobbeschreibung

We are currently partnered with a highly technical AI research organisation working on advanced machine learning systems and large-scale model development. They are looking to hire a Senior Machine Learning Research Scientist to design, develop, and evaluate innovative ML models and methodologies for complex research problems.

The role combines theoretical and practical machine learning research, working closely with researchers, mathematicians, and ML engineers to translate theoretical developments into practical algorithms, develop rigorous experimental methodologies, and evaluate models at frontier scale.

Key responsibilities

• Propose, design, and implement novel machine learning models and methodologies for complex research problems
• Collaborate with mathematicians and specialist research scientists to translate theoretical developments into practical ML algorithms and models
• Adapt and fine-tune existing frontier models for specific applications, domains, and research scenarios
• Design and implement rigorous experimental protocols and evaluation frameworks
• Develop reproducible experiments capable of operating at the scale and complexity required for frontier models
• Analyse and interpret experimental results to identify new research directions and inform future hypotheses
• Benchmark and optimise model performance, efficiency, and resource utilisation

Key requirements

• Advanced degree in Computer Science, Mathematics, Machine Learning, or a related discipline
• 5+ years of experience working on deep learning research projects, particularly involving large-scale or frontier models
• Demonstrated experience training, adapting, and/or fine-tuning large-scale machine learning models
• Experience with model adaptation techniques such as transfer learning, domain adaptation, or meta-learning
• Proven track record of contributing to high-quality machine learning or deep learning research
• Strong expertise with ML frameworks such as PyTorch, TensorFlow, or JAX
• Experience developing, training, and evaluating ML models in distributed computing environments
• Strong Python development skills, including research-quality and production-grade code
• Experience in Natural Language Processing (NLP)
• Experience with probabilistic graphical models or related statistical modelling techniques
• Publications or other demonstrable contributions to high-quality deep learning research
• Experience with large-scale distributed training and inference infrastructure

Keywords

Senior ML Research Scientist / Senior Machine Learning Research Scientist / ML Research Scientist / Machine Learning Research / Artificial Intelligence Research / Deep Learning / Machine Learning / Frontier Models / Large-Scale Models / Large Language Models / Model Development / Model Training / Model Fine-Tuning / Model Adaptation / Transfer Learning / Domain Adaptation / Meta-Learning / Model Evaluation / ML Evaluation / Evaluation Frameworks / ML Benchmarks / Alignment / AI Research / Advanced AI / Experimental Methodology / Experimental Design / Research Methodology / Distributed Computing / Distributed Training / Distributed Inference / Large-Scale Training / Large-Scale Inference / Training Optimisation / Inference Optimisation / Model Performance / Computational Efficiency / Resource Optimisation / PyTorch / TensorFlow / JAX / Python / Experiment Tracking / Reproducible Research / Version Control / NLP / Natural Language Processing / Probabilistic Graphical Models / Statistical Modelling / Deep Learning Research / Machine Learning Algorithms / Research Engineering

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