Machine Learning Engineer — 6-Month Contract

Role overview Take machine learning work from problem definition through deployment and ongoing monitoring during a six-month contract. You’ll build models that address real client needs and keep them reliable in production, paying close attention to data quality, evaluation, and changes in real-world inputs.

Responsibilities - Translate business questions into machine learning problems, then build, evaluate, and deliver models. - Own the supporting lifecycle, including data pipelines, training, deployment, and monitoring. - Develop evaluation methods that reflect how well a model performs in production. - Detect data or model drift and respond through retraining or rollback when appropriate. - Work with clients and product partners to confirm that model objectives address the underlying need.

Requirements - At least four years building and deploying machine learning systems in production. - Strong Python skills and experience with practical ML tools such as scikit-learn, pandas, and a deep-learning framework. - Solid understanding of data modeling, feature engineering, and reliable model evaluation. - Ability to communicate trade-offs clearly and deliver value quickly in a contract setting.

Nice to have - Experience with MLOps tools and serving models reliably at scale. - Familiarity with cloud infrastructure and end-to-end data pipelines. - A research paper, competition result, or production model you can discuss with confidence.

Benefits and work setup - Six-month contract with a defined scope and potential to extend. - Fully remote across EU or Americas time zones, with async-friendly work and agreed overlap hours. - End-to-end ownership of ML problems and a hardware and compute budget.