Machine Learning Engineer

You will take machine learning work from a notebook to something running in production. That means preparing data, training and evaluating models, and then making them available through an API that other systems can call.

Our projects vary. Some use classic ML on tabular data, some use language models or embeddings. We care less about the newest paper than about whether the model works on real data and keeps working after launch.

The work:

• Prepare and clean datasets
• Train, tune and evaluate models, and report the results honestly
• Deploy models behind APIs
• Monitor accuracy and cost once they are live
• Explain results and limits to people who are not engineers

• 3 or more years working on machine learning in a real setting
• Strong Python, with pandas and scikit-learn, and PyTorch or TensorFlow
• Experience evaluating models properly, not just reporting accuracy
• Able to deploy a model as a service
• SQL

Nice to have:

• Experience with embeddings, vector search or fine-tuning language models
• MLflow or similar experiment tracking
• Cloud experience on AWS, GCP or Azure