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Staff Machine Learning Engineer

CDI
Paris
Salaire : Non spécifié
Télétravail non autorisé
Expérience : > 5 ans

Philips Health Technology Innovation Paris
Philips Health Technology Innovation Paris

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Le poste

Descriptif du poste

What you’ll do

We are looking for an experienced machine learning (ML) engineer to own the strategy behind Cardiologs' environment for ML development. You will ensure continuous training of ML models and tracking of their performance. You will also set up or develop tools to facilitate the development by other teams of algorithms that are used to streamline the diagnosis of several thousands of patients daily.

You will:

- set up continuous training of deep learning models at scale across multiple machines;

- develop dataset management tools to allow continuous improvement and ensure reproducibility;

- improve evaluations of current and future machine learning models to ensure non-regression and track improvements;

- set up existing tools, or develop internal ones to facilitate fast and reliable ML pipeline development by other teams;

- and optimize ML pipelines in production in terms of speed and reliability.

You will also :

- build your team roadmaps in consensus with other stakeholders;

- set a nice work environment for your team, in line with our values;

- stay up-to-date with data engineering industry standards;

- and participate in knowledge-sharing events with the rest of the research team.

Success in this role also requires a good understanding of the way of working of the data science teams. Experience with Data Science will be valuable in this regard.

Who you are

- You have at least 5 years of experience in data science or software engineering.

- You have at least 2 years of experience and a proven track record building / setting up / maintaining tools for Machine Learning in a tech company.

- You have already worked with Python, Git, deep learning frameworks, machine learning tools (MLFlow, Kubeflow, TensorFlow Serving, etc.), cloud services, databases.

- Your working style can be described as collaborative, autonomous, proactive, and structured.

- You are considered a reference by your peers in your domain of expertise.

- You have excellent communication skills.

- You write and speak both French and English.

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