Machine Learning Engineer

Job description

About the role

As a Machine Learning Engineer, you will have the opportunity to build a secure application for collaborative federated machine learning. This product, called Connect, enhances the collaboration between data experts (e.g., medical expert, data engineer) and data scientists across multiple data centers. Connect makes it possible to train a machine learning model across multiple data centers storing highly sensitive data (federated learning). For more details, have a look here!

Connect is part of the Data Platform, a fast growing team composed today of 50 people, which secures access to rich multi-modal data at scale to enable discovery and development of new treatments, internally and in collaboration with pharma partners.

You’ll work in a team of Software and ML Engineers in close collaboration with the product team, data scientists and operations team. You will report to the Software Engineering Lead and you will actively contribute to the technical design and implementation of the APIs and libraries of the platform.

In particular, you will:

• Develop libraries to facilitate data scientists interactions with the platform

• Collaborate with a team to design and develop the platform Design and implement state of the art federated learning strategies. Design and implement privacy enhancing technologies.

• Work on key initiatives to keep a high productivity — such as improving our code, tests, and promoting new tools

Preferred experience

About you

Required qualifications:

• A good experience as a Machine Learning or backend Software Engineer

• Strong experience with Python and standard Python ML libraries (PyTorch, TensorFlow, Numpy, Pandas)

• Knowledge of Data Engineering and Machine Learning

• Ability to work in an international environment and communicate in English

• Strong team spirit

Bonus:

• Experience in DevOps and MLOps

• Experience working with distributed frameworks (Spark, Dask …)

• Open source contributions

• If you are interested in joining us but don’t check all the boxes, we still encourage you to apply as we are seeking to build a multidisciplinary team with diverse backgrounds.