Entrepreneurship in the territories: is it the right time?
Join us and be a pioneer for a green transport revolution.
Automotive Cells Company (ACC) is one of Europe’s newest and most exciting high-tech companies. Backed by Saft-Total, Stellantis-Opel and Mercedes-Benz, ACC is set to power the future of the automotive industry by innovating in battery technology.
We aim to produce sustainable, affordable, high-capacity, longer-life batteries as a cleaner alternative to current energy sources. We have created an R&D center and new state-of-the art facility in France (New Aquitaine), and we are building gigafactories in Hauts de France, Germany and Italy.
We need a range of skilled and agile people to bring our vision to life, especially in the areas of industrialization, mechanical design, testing/prototyping and any other function of a new-born company. If you’re looking to take your career further than you imagined, if you’re passionate about creating cleaner transport, we’d like to hear from you.
Our core Values are : Pioneering Spirit, Fast & Agile, Excellence, Greener & Cleaner !
We are also very proud of our 2023 CSR Report : https://www.acc-emotion.com/stories/accs-2022-corporate-sustainability-report
Accelerating sustainable mobility for all.
Are you passionate about data science AND software engineering?
Do you enjoy bringing machine learning models to life, putting them in production, and witnessing their impact for the company?
As a Machine Learning Engineer at ACC, you will be tasked with carrying out product developments involving data science, all in a strong spirit of collaboration with other data scientists and stakeholders. You will be part of a data team composed of several data profiles (data scientists, data analysts, data engineers, ML engineers, data product managers, business data owners) with a culture where sharing knowledge is centric.
Principal accountabilities :
- Engage in machine learning projects specifically tailored to the industrial battery manufacturing sector, such as optimizing battery life, improving manufacturing processes, or enhancing product quality.
- The whole lifecycle of an Machine Learning project, from wrapping up models for apps deployment to functional/operational monitoring (setup features and data drifts alerts, detect outliers, monitor system performance metrics).
- MLOps implementation as part of CI/CD systems together with the DevOps engineers.
- Handle upstream and downstream services as you will serve/make requests in real-time and return/receive results in batches or as a stream supporting hybrid on prem and cloud architecture.
- Mentor teammates, share your expertise, especially with Databricks.
