Innovation Data Engineer

About this role :

• We are currently looking for an Innovation AI Junior Engineer to join our Process Innovation team based in our Innovation Center in Grenoble, France.
• As such, you will be responsible for developing innovative solutions based on cutting-edge technologies and solving practical problems. Your main work will be to understand the cases and do investigations with versatile resources, then turn the solution and technology from either a lab or concept to real production with support from supervisors.
• You will mainly focus on quality, efficiency, and unmanned topics to make Verkor a strong, competitive battery manufacturer.

Main responsibilities :

• 1. Identify the problem, simplify it, and summarize it into an engineering model with support from experts.
• Recognize the problem beneath phenomena;
• Understand causal relationship and other priori knowledge related to the scenario;
• Breakdown problems into potential solvable tasks;
• 2. Define requirements, and investigate potential solutions.
• Clarify goals for each task;
• Develop roadmap of whole solution;
• Research available approaches and classify technical routes;
• Analysis risks and ROI;
• 3. Design and validate
• Propose concepts, drawing a whole solution;
• Provide DoE of your design;
• Select required components and software, etc.;
• Initiate purchase or self-develop for core functionalities;
• Verify feasibility and offer deployable solution for production lines.
• 4. Report and support
• Report progress and results of the studies to other Verkor departments.

Requirements :

• Bachelor or Master's degree in Computer Science, AI, or similar discipline
• 1 year minimum of experience working with AI and innovation projects. Industrialization experience is mandatory. Experience related to batteries is more preferred.
• Experience in Agile based software development is required
• Mandatory knowledge on SQL, MySQL databases
• All necessary techniques for data mining is required, such as data extraction, feature engineering, etc.
• Proficiency in machine learning techniques is required; DL&RL is a plus
• Strong knowledge on Scikit-learn, Pandas, and familiarity with at least one DL frameworks such as PyTorch, Keras, etc.
• R, & Matlab knowledge
• Strong knowledge on Python, C++
• Knowledge on time series forecasting techniques
• Good learning skills