Machine Learning Engineer
$80,000–$90,000 year
On-siteFremont, California, United States
Job Summary
Design and implement novel machine learning and deep learning models tailored to internal research needs, focusing on advanced materials, electrochemical systems, and high-throughput data environments. Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures, while conducting rigorous experimentation, benchmarking, and ablation studies. Collaborate with cross-disciplinary R&D teams and battery scientists to incorporate physical constraints into modeling, contribute to internal documentation, and present research outcomes to technical and leadership teams. Track and integrate advances from the ML research community to ensure technical excellence. This fully on-site role in Manteno, IL requires a Ph.D. or M.S. in a relevant field with expertise in Python and PyTorch.
Required Qualifications
- 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
- Excellent communication, collaboration, and problem-solving skills in interdisciplinary environments
Desired Qualifications
- Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains
- A publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR)
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