Machine Learning Engineer
Core
Design and implement novel machine learning and deep learning models for advanced battery products and energy storage systems.
Role type
Machine Learning Engineer (Scientific Domain)
Builds
Production ML models for electrochemical systems and high-throughput data environments
Domain
Energy storage, electric vehicles, battery technology, materials science
Deliverable
production ML models
Required skills
Model architecture design, algorithm development, Python, PyTorch, TensorFlow, learning theory, experimentation, benchmarking, ablation studies
Preferred skills
Scientific domain knowledge (battery/energy), time-series data experience, publication record in top-tier ML conferences
Technologies
PyTorch, TensorFlow, Transformers, LLMs
Responsibilities
Design and implement novel ML/DL models; Prototype and evaluate state-of-the-art algorithms; Conduct rigorous experimentation and benchmarking; Collaborate with domain experts to incorporate physical constraints; Track and integrate advances from the ML research community
Seniority
Mid-Senior, hands-on IC