Tech Stack

Description

You will collaborate with senior AI/ML engineers to develop downstream applications based on a multi-modal battery foundation model, including cell quality assessment, production optimization, and performance prediction. Analyze complex datasets, apply machine learning and deep learning techniques for model training and optimization, and work with cross-functional teams to implement technical solutions.

Requirements

• Master's degree in CS, EE, Statistics, or related field
• 3+ years experience in ML/AI (manufacturing or battery preferred)
• Proficiency in Python, TensorFlow, PyTorch
• Experience with tabular, time series, and image data
• Strong communication and problem-solving skills

Responsibilities

• Develop downstream applications from multi-modal battery large model
• Optimize models for cell quality, production process, and performance prediction
• Implement and optimize data processing pipelines
• Apply ML/DL techniques for model training and evaluation
• Analyze complex datasets to extract features for model improvement