Job Description
A Machine Learning Engineer role focused on designing and developing advanced ML models to support battery technology and energy storage systems, collaborating with interdisciplinary teams to address real-world scientific challenges in a fast-paced, innovative environment.
Key Responsibilities
- Design and implement novel machine learning and deep learning models for research needs
- Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid architectures
- Conduct experimentation, benchmarking, and ablation studies on ML models
- Collaborate with battery scientists and domain experts to incorporate physical constraints into models
- Contribute to internal documentation and present research outcomes to technical and leadership teams
- Track and integrate advances from the ML research community to maintain technical excellence
Requirements
- A Ph.D. preferred or M.S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field.
- Demonstrated expertise in model development, optimization, and algorithmic innovation.
- Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc.
- Solid understanding of learning theory concepts such as regularization, generalization, loss functions, and evaluation metrics.
- Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains, is highly desirable.
- A publication record in top-tier ML conferences e.g., NeurIPS, ICML, ICLR, CVPR is a strong plus.
- Excellent communication, collaboration, and problem-solving skills in interdisciplinary environments.
Benefits & Perks
Compensation/salary range: $80,000 - $90,000
Bonus benefits: 15% bonus
Work environment perks: Fully on-site role in Manteno, IL
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