Gotion, Inc.

Gotion, Inc.

Machine Learning Engineer

Fremont, California · Full-time

Sponsorship not specified$80k-$90kDetected 23 hours ago
PythonAlgorithmsMachine LearningDeep LearningTensorFlowPyTorchNLPLLMsA/B TestingElectrical EngineeringResearchLeadershipCommunicationCollaborationProblem Solving

Stay score

odds of building a lasting career here

47Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level II)66
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~30% per draw at Level II). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level I · 1×
Level I$137,0931 entry
Level II$165,1312 entries
Level III$193,1493 entries
Level IV$221,1874 entries

The bottom of this range ($80,000) is below the Level I prevailing wage of $137,093. An H-1B cannot be filed below the prevailing wage, so an offer at the floor of this band could not be sponsored as posted.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

4 transfer filings in the last year, covering 4 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures
  • Conduct rigorous experimentation, benchmarking, and ablation studies
  • Contribute to internal documentation and present research outcomes to technical and leadership teams

Responsibilities

  • Collaborate with battery scientists and domain experts to incorporate physical constraints or scientific priors into modeling
  • 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.

Requirements

  • Demonstrated expertise in model development, optimization, and algorithmic innovation
  • Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc.
  • Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains, is highly desirable

Nice to have

  • A publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR) is a strong plus

Compensation

  • The US base salary range for this full-time position is $80,000.00 - $90,000.00 + 15% bonus + benefits.

Benefits

  • Design and implement novel machine learning and deep learning models tailored to internal research needs

Company info

  • 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.

This listing is sourced directly from Gotion, Inc.'s careers page and normalized into a canonical job model.