Gotion, Inc.
Machine Learning Engineer
About this role
Gotion Inc. seeks a Machine Learning Engineer to design and deploy novel ML models for battery technology and energy storage systems. Based in Manteno, IL on a fully on-site basis, you'll collaborate with R&D teams to develop deep learning solutions that incorporate physical constraints and advance the company's next-generation EV and ESS product lines.
What you'll do
- Design and implement custom machine learning and deep learning models for battery research applications
- Prototype and evaluate state-of-the-art algorithms including Transformers, LLMs, and hybrid architectures
- Conduct experimentation, benchmarking, and ablation studies to validate model performance
- Partner with battery scientists to integrate physical constraints and domain knowledge into models
- Document research findings and present technical outcomes to leadership and cross-functional teams
- Monitor ML research advances to maintain technical excellence and innovation
What they're looking for
- Machine learning model architecture and design
- Python and ML frameworks (PyTorch, TensorFlow)
- Deep learning (Transformers, LLMs, hybrid models)
- Time-series and scientific data analysis
- Learning theory (regularization, generalization, loss functions)
- Experimentation and benchmarking methodology
- Cross-disciplinary collaboration and communication
- Battery/materials/energy domain knowledge (preferred)
Benefits
- 15% bonus structure
- Health insurance and related benefits
- On-site work environment in Silicon Valley-connected company
- Opportunity to work on cutting-edge EV and energy storage technology
- Collaborative R&D culture with domain experts
- Access to global R&D centers in Ohio, China, Japan, and Europe
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Gotion, Inc.
Gotion, Inc. manufactures large-scale lithium battery cells and packs for electric vehicles and energy storage systems, with a major 40GW facility under construction in Illinois. The company is hiring mechanical, electrical, thermal, and systems engineers to design and commission manufacturing infrastructure, quality control systems, and battery thermal performance.
- Website
- gotion.com
Likely interview questions
- Walk us through a machine learning model you designed from scratch—what was the problem, your approach, and how did you validate performance?
- Describe your experience with Transformers or LLMs. How have you adapted these architectures for your specific use case?