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Principal TLM - ML Data Infrastructure

Job in Sunnyvale, Santa Clara County, California, 94087, USA
Listing for: Generalmotors
Full Time position
Listed on 2026-10-09
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Engineering, AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 275000 - 348000 USD Yearly USD 275000.00 348000.00 YEAR
Job Description & How to Apply Below
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’returning today’sim possible 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 peopleas 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.
  • Utilise 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 compensation may not be representative for positions…

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