Machine Learning Engineer

Requirements

• We are looking to hire an ambitious and highly analytical Machine Learning Engineer (f/m/d) based in Berlin

• This role is ideal for you if you combine a strong technical background in machine learning with hands‑on software engineering experience, and are eager to create real impact in a fast-growing health tech startup - working closely with our cross‑functional AI, product, and business teams

• You hold a Bachelor's or Master's degree in Computer Science, Machine Learning, Mathematics, or a related field

• You bring 2+ years of hands‑on professional experience in machine learning and have a proven track record with modern ML frameworks (PyTorch, TensorFlow)

• You ideally have practical experience in Computer Vision, NLP (Natural Language Processing), Time Series Analysis, or Reinforcement Learning

• You possess strong programming skills in Python and are highly familiar with scientific computing libraries (NumPy, Pandas, Scikit‑learn)

• You have solid experience with version control (Git), collaborative development, and Python packaging and dependency management (Poetry, uv)

• You are experienced in Docker containerization, comfortable applying MLOps practices (MLflow, DVC), and skilled in data engineering tools (Meltano, Airflow, Metabase)

• You bring web development skills (FastAPI, Flask, Django) for building robust ML APIs and have experience developing CI/CD pipelines for ML workflows

• You are fluent in English and possess excellent communication skills to thrive in a cross‑functional environment

What the job involves

• In this role, you will drive our AI initiatives by designing, deploying, and maintaining advanced computer vision models for medical image analysis

• Design, train, and evaluate computer vision models for medical image analysis using PyTorch and PyTorch Lightning

• Monitor production models, optimize performance metrics, and proactively implement retraining strategies to address model drift

• Perform data preprocessing, augmentation, and quality control in close collaboration with data annotators and medical advisors

• Systematically maintain organized datasets, model versioning (FiftyOne, DVC), experiment tracking (MLflow), and automated testing

• Build and maintain scalable ML pipelines and APIs (FastAPI/Flask) utilizing CI/CD pipelines, containerization (Docker), and MLOps practices for automated workflows

• Collaborate closely with frontend and backend engineers to integrate AI models smoothly into product workflows

• Build and maintain ELT pipelines (Meltano), orchestrate workflows (Airflow), and create dashboards and visualizations (Metabase) for actionable model insights and business metrics

• Ensure high code quality through version control (Git), thorough code reviews, and comprehensive documentation of models, experiments, and best practices

• Work cross-functionally within the AI, product, and business teams, and present your findings effectively to both technical and non-technical stakeholders