Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 6 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Apr 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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What Gotion INC paid sponsored hires in similar roles1 certified filing for “Senior Battery CAE Engineer” (Mechanical Engineers) in CA: $185k–$185k, median $185k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 6 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Apr 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Gotion INC paid sponsored hires in similar roles
- 1 certified filing for “Senior Battery CAE Engineer” (Mechanical Engineers) in CA: $185k–$185k, median $185k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. The pay stated here ($80,000.00 - $90,000.00) is below what this employer usually pays sponsored hires for this role. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
Gotion Inc. is based in Silicon Valley, CA, currently building a Manufacturing facility in Manteno, IL and has R&D centers in Ohio, China, Japan and Europe. We innovate in the next generation electric vehicle and energy storage technologies (lithium batteries and related systems) with the aim to accelerate electrified transportation and achieve sustainable development. Gotion is powered by a leading power battery technology company that provides solutions for vehicles including the world's first mass commercial e-bus route.
Gotion is a career destination - we are not simply attempting to just fill another job, but to pursue a dream of global green energy together! We offer outstanding opportunities to individuals seeking an exciting and challenging working environment. Everyone is highly valued and plays a vital role in the growth of our organization.
About The Team
The Product Development Team at Gotion Illinois 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 Manteno, IL 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 $80,000.00 - $90,000.00 + 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 locati
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