About The Team The Product Development Team at Gotion Inc., New Energy Inc. focuses on the design and development of advanced battery products for next-generation energy storage system (ESS) and electric vehicle (EV) applications. We lead the full product development cycle, integrating mechanical, electrical, thermal, and control system to create high-performance battery solutions, along with comprehensive system integration, validation, and certification activities.

Role Summary

We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains such as battery technology, energy systems, or related physical sciences. This is a fully on-site role based in Fremont, CA focused on building innovative ML models from the ground up.

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine learning solutions that address real-world challenges in advanced materials, electrochemical systems, and high-throughput data environments.

Essential Duties and Responsibilities:

• Design and implement novel machine learning and deep learning models tailored to internal research needs
• Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures
• Conduct rigorous experimentation, benchmarking, and ablation studies
• Collaborate with battery scientists and domain experts to incorporate physical constraints or scientific priors 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

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
• 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

The US base salary range for this full-time position is $110,000.00 - $135,000.00 + 15% bonus + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.