Job's summary

We are looking for a Machine Learning Engineer to join the Team. As a Machine Learning Engineer at Resilience you will have the opportunity to work on the entire data cycle, exploring, enriching, preparing, analyzing, modeling and industrializing new features based on ML algorithms. You will basically participate to enrich all of our products thanks to AI.

Il you are passionate about extracting value from data, finding the most adapted models and bringing them to industrialization to answer business challenges, you are in the right place!

How your job participates to make Resilience successful:

As a patients-centric company we believe that new machine learning techniques can definitively participates to improve their daily life. At Resilience, we all share one global common objective and you will participate to achieve it: reinvent care and improve patients quality of life.

What your day to day looks like:

Most of your time will be dedicated to the improvement and enrichment of an existing product using NLP techniques and more to solve data usability issues within our healthcare system. For this you will have to design solutions that are both pragmatic and constrained for short term efficiency, using more classical approaches, as well as ambitious and more exploratory for mid/long term plans.

To do this you will be sharing thoughts and code with the rest of the team (during the usual SCRUM ceremonies or not) as well as external contributors (like M.D. or product managers). You can also expect to be exposed to various other subjects (clinical studies, other features...) as the team participates in several different efforts within the company (e.g. patients' adverse events anticipation).

Lastly, the company operates fully remotely with offices in various hubs (such as Paris, Biarritz, etc.). Although the team is entirely based in Paris, expect a significant amount of asynchronous communication.

About the Team

The Team is currently composed of Machine Learning Engineers and Data Scientists. You will have the opportunity to collaborate with many different teams across R&D (Product, Data Engineering, SRE…) but not only (Medical…).

Targeted profile

⚙️ You are the good person if you already have experience with:

• Python and standard ML packages (pandas, numpy, scikit-learn etc)

• NLP projects and with some of the most common packages (spaCy, NLTK etc)

• Traditional statistical learning as well as machine learning techniques, inc. supervised and unsupervised learning

• Sourcing, cleaning, manipulating and analyzing data

• Models industrialization, e.g. putting models in production and monitoring their performance

🙂 You are the good person if you are:

• Pragmatic, analytic, solution-oriented, proactive mindset

• Strong team player and ease collaboration with business teams

• Interested by health ecosystem

• Good communicator and able to adapt your speech according to the audience, both written and oral

It is even better if you:

• Are able to go beyond his regular technical scope if necessary

• Are familiar with web API framework (FastAPI or equivalent) and serving ML models to applications

• Are proficiency in DevOps environment : versioning (Git), CI/CD, test coverage, containers etc.

• Are proficiency in MLOps and ML Platform : experiment trackers, orchestrators, monitoring & measurement, data lineage etc

• Have former experience processing non-structured health data

• Have practical knowledge in one of the popular machine learning and deep learning frameworks (TensorFlow, PyTorch, Keras, etc)

• Have knowledge of experience with front-end data visualization

Recruitment process

• Interview 1 with Ivan (Data & Machine Learning Lead, your future manager) or Jullian (Head of date) - to make sure you are all aligned on the offered position

• Technical Async Test with Ivan: coding test

• Technical Live Test with Ivan & Jullian: system design test

• Interview 2 with Raphaëlle (Product Data Lead) - to assess collaboration between Product & Business teams

• Interview 3 with Alice, talent manager - to share about company’s culture

GDPR : Your personal data will be processed for the purposes of recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results thereto, and as is otherwise needed in the recruitment and hiring processes. They will be available only for people involved in the process and erased after 2 years of inactivity.

Under GDPR and as Resilience attach great importance to privacy, please note that you have the right to request access to your personal data, to request that your personal data be rectified or erased. The Data Protection Officer can be contacted at privacy@resilience.care

For more information, please check our privacy policy.