We are looking for a skilled Machine Learning Engineer to join our cross-functional engineering team in Berlin, Germany. This contract position is for 12 months and is renewable. You will be responsible for designing, developing, and optimizing machine learning pipelines and large-scale data systems that empower researchers, data scientists, and engineers to train, evaluate, and deploy advanced AI models, including Large Language Models (LLMs). Collaborating with international teams, you will play a vital role in creating scalable systems for data processing, automated annotation, experimentation, and model training, ensuring efficient development and deployment of machine learning initiatives in both controlled and real-world environments.

Responsibilities

• Collaborate with science and engineering teams to develop systems that support reliable AI reasoning with LLMs.
• Create systems for automatic dataset generation and annotation using reasoning engines, simulators, and AI planning tools.
• Design and maintain scalable data pipelines for training and fine-tuning machine learning models.
• Manage large-scale datasets, including preprocessing, post-processing, and data lake infrastructure.
• Develop and optimize automated workflows for data processing and model experimentation.
• Build experimental frameworks and test environments for running machine learning experiments across various domains.
• Utilize cloud infrastructure and distributed computing resources to support large-scale machine learning workloads.
• Engage in Agile/Scrum development within an international engineering team.

Requirements

• Strong experience with machine learning frameworks such as PyTorch, TensorFlow, or Keras.
• Proficiency in Python for scripting, automation, and machine learning development.
• Strong SQL skills and experience with large-scale datasets.
• Familiarity with cloud computing platforms, particularly AWS (S3, EC2, Redshift, SageMaker, Lambda).
• Minimum of 3 years of experience in machine learning engineering, analytics, or data engineering roles with increasing technical responsibility.
• Experience in designing and executing end-to-end data and modeling workflows.
• Strong understanding of experimental design and the ability to analyze results for cause-and-effect relationships.

Nice to Have

• Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Experience in training and deploying deep learning or machine learning models.
• Experience with very large datasets (multi-terabyte scale).
• Strong knowledge of statistical analysis and experimental design methodologies.
• Experience in building scalable machine learning infrastructure and experimentation frameworks.