Machine Learning Engineer

My client, a fast-growing AI startup in Berlin, is transforming how biopharma companies analyze complex biomedical data. Their mission is to accelerate drug discovery and clinical decision-making through cutting-edge machine learning and data engineering. They're backed by top-tier European investors and are now expanding their technical team.

We're looking for a Machine Learning Engineer with a strong foundation in both modeling and systems, ideally with exposure to biological or pharmaceutical data environments.

🔧 What You’ll Do

• Design, train, and deploy ML models on large-scale biomedical and clinical datasets
• Build end-to-end data pipelines to process structured and unstructured biopharma data
• Collaborate with data scientists, domain experts, and engineers to refine and productionize algorithms
• Own and improve core infrastructure for model monitoring, versioning, and reproducibility (MLOps)
• Explore new techniques (transformers, graph models, time-series) for predicting biological or therapeutic outcomes

🧰 Tech Stack You Might Use

• Languages: Python, SQL
• ML Frameworks: scikit-learn, PyTorch, TensorFlow, Hugging Face
• Data Tools: Pandas, Apache Arrow, Airflow, dbt
• Deployment: Docker, FastAPI, AWS/GCP
• MLOps: MLflow, DVC, GitHub Actions

✅ What We're Looking For

• 2+ years of experience as an ML Engineer, Data Scientist, or similar
• Strong grasp of ML fundamentals and experience shipping models to production
• Comfortable with building data pipelines and working with large, messy datasets
• Curiosity about biology, healthcare, or pharmaceuticals (prior experience a bonus)
• Startup mindset—hands-on, proactive, and open to fast-paced environments

💡 Bonus (Nice-to-Haves)

• Experience with bioinformatics, clinical trials, or pharmaceutical data
• Familiarity with generative models or transformer architectures
• Exposure to compliance or regulated environments (GxP, HIPAA, etc.)

🚀 Why Join?

• Work on real-world problems with a clear societal impact
• Be part of a high-trust, no-politics culture with deep technical talent
• Competitive salary, equity options, and flexible hybrid/remote work setup