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ML Ops Engineer

Postée le 04 mai

Lieu : Paris · Contrat : CDI · Rémunération : A négocier

Société : AQEMIA

Aqemia is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline. Our mission is to design fast innovative drug candidates for dozens of critical diseases. Our differentiation lies in our unique quantum and statistical mechanics algorithms fueling a generative artificial intelligence to design novel drug candidates. The disruptive speed and accuracy of our technological platform enables us to scale drug discovery projects just like tech projects.

We are now a team of 40 mission-driven, fast-paced people at the crossroads of Chemistry, Machine Learning, Physics and Software Engineering, and have raised $12M with leading VCs.
If this sounds exciting to you, come and join us!

Description du poste

As an ML-Ops Engineer, you will manage models' life-cycles and help our teams make the most of them in drug-discovery projects.
You will join a team of 8 Machine Learning Engineers and work in multidisciplinary project teams with chemists, data and software engineers, to solve complex problems with large amounts of biological and chemical data.

You will :
- Design, benchmark and implement all the steps of models’ lifecycle: distributed data-processing and training, large scale inference, model monitoring…
- Build benchmark datasets with ML engineers, chemists and physicists, and automate the quality control of new models
- Work with ML engineers to optimize deep neural networks on graphs and geometric data (eg. neural networks compilation, hyperparameter tuning pipelines…)
- Propose and implement innovative solutions to speed up the feedback loop from experimental results to new model versions
- Take part to strategic discussions about designing a new solution vs resorting existing tools
- Share best practices, literature and most recent developments in the ML-Ops field within the ML team.
- Help us find the best solutions with your experience and understanding of our use-cases

Profil recherché

You have strong skills in Python and Docker. You have in-depth knowledge of the ML-ops lifecycle, good understanding of the theoretical foundations of machine learning and in-depth knowledge of open-source ML-Ops tools and curiosity to follow and test new developments in the field. You are familiar with the common packages used to design and train machine learning models, especially deep neural networks. You have experience with one the major cloud platforms AWS, GCP or Azure and with continuous integration and deployment (CI/CD) frameworks. It is a plus if you have experience with deep learning compilation frameworks. You have interest for life sciences and willingness to learn from domain experts
You should join us if you want to solve difficult problems on topics that really matter and if you are passionate about what you do and enjoy sharing your knowledge. If you want to build a ML platform with a small team and bring your own impact in drug discovery and if you want to combine the rigor of large companies ML platforms with the speed of a startup, you should apply now.

Pour postuler :

Should you wish to apply for this position please send us your resume at careers@aqemia.com

We are growing fast, if you feel that you don't fit this job description but you’re still excited to join, then please get in touch!