Jobs / United States / General Motors Company
Principal TLM - ML Data Infrastructure
General Motors Company · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- 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. 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 General Motors Company paid sponsored hires in similar roles2 certified filings for “Senior ML Engineer - Embodied AI Offboard Percepti” (Data Scientists) in CA: $230k–$240k, median $235k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
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.
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. We are seeking a highly skilled and experienced Principal TLM (Technical Lead Manager) to lead the development and optimization of our Machine Learning (ML) Data Infrastructure. This role is crucial for enabling cutting-edge AI solutions and driving data-driven innovation across General Motors. What You'll Do: * Lead and manage a team of engineers in the design, development, and maintenance of scalable and robust ML data infrastructure, ensuring high performance, reliability, and security. * Define and implement architectural patterns and best practices for data ingestion, processing, storage, and access within the ML ecosystem, utilizing Agile Methodology. * Collaborate with ML engineers, data scientists, data platform engineers, and product teams to understand data requirements and translate them into technical specifications for the data infrastructure. * Conduct in-depth analysis of existing systems, identifying bottlenecks and opportunities for improvement in data pipelines and analytical platforms. * Utilize strong understanding of data pipeline development and existing and upcoming technologies to design efficient data flows and system architectures. * Oversee the evaluation and integration of new technologies and tools to enhance the ML data infrastructure capabilities. * Provide technical guidance and mentorship to junior engineers, fostering a culture of innovation and continuous learning. * Work with relevant partners to ensure compliance with data governance policies, security standards, and regulatory requirements. * Participate in strategic planning and road mapping for the ML data infrastructure, aligning with overall company objectives. * Proactively identify and address potential issues, demonstrating a Detail-Oriented approach to problem-solving. * Utilize Qualitative Research to understand user needs and inform infrastructure development. Your Skills & Abilities: * Bachelor's or Master's degree in Computer Science, Engineering, or a related field. * 10+ years of experience in data engineering, software development, or a related field with a focus on Machine Learning (ML) data infrastructure. * Proven experience in leading and managing technical teams. * Deep expertise in designing, building, and operating large-scale data systems and Analytical Platforms. * Proficiency in multiple Computer Languages relevant to data engineering (e.g., Python, Scala, Java). * Strong understanding of Artificial Intelligence (AI) and Machine Learning (ML) concepts and their data requirements. * Demonstrated ability in Determining System Requirements and translating them into technical solutions. * Solid understanding of Agile Methodology and experience working in an agile environment. * Excellent analytical, problem-solving, and communication skills. * Highly Detail-Oriented with a commitment to quality and accuracy. Preferred Qualifications: * Previous experience in Robotics or Autonomous Driving. Remote/Hybrid: This role is categorized as fully remote or hybrid. Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compen