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Sr. Machine Learning Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: generalmotors
Full Time position
Listed on 2026-10-05
Job specializations:
  • Engineering
    AI Engineer (Applied/Software), Robotics, Systems Engineer, Embedded Software Engineer
Salary/Wage Range or Industry Benchmark: 175000 - 250000 USD Yearly USD 175000.00 250000.00 YEAR
Job Description & How to Apply Below
Job Description
The Role

GM is developing the next generation of embedded platform software to deliver state-of-the-artADASfeatures to our customers.

We are looking for an expert Sr. Camera ISP Engineer to join our Autonomous Vehicleteam and help us build the best self-autonomous system in the world. In this position, you will be part of the Autonomy Interface Software team, whichis responsible for developing cameradata pipelines for autonomous vehicles. You will interact with camera hardware engineers, embedded software engineers, systems engineers,Embodied AI engineers, technical program managers internally, and variousexternalimagercomponentvendorsto ensure high-quality cameras are designed, manufactured, and tuned.

You will be working closely with an embedded software team to enable Camera ISP functionality on new hardware.

If you are looking to solve one of today’s most complex engineering challenges, see the results of your work in hundreds of self-driving cars, and make a positive impact in the world, join us.

What You’ll Do
  • Responsible for delivering Camera Image Signal Processing (ISP) tuningoptimizedfor autonomous vehicle use-cases
  • Work closely with cross-functional teams and external vendors on specifications, system definition, software development, and image quality tuning and evaluation
  • Design and execute comprehensiveobjectiveand subjective image quality evaluations using lab charts and real-world scenes, selectingappropriatemetricsand analyses for each,leveraging tools such as Imatestand other chart/scene-based analysis methods, and developing GM-specific test scripts and IQ specification analysis tools.
  • Solid understanding of image sensors to optimize HDR sensor configurations and ISP settings for autonomous driving scenarios, aligningobjectivesand success metrics across EAI, system, and sensor teams.
  • Work with sensor validation and vehicle fleet teams to perform ISP characterization, image qualitytuningand evaluation, and troubleshootimage quality related issues
  • Collaborate with machinelearningengineersand hardware teams to architect sensing strategy for autonomous vehicles at scale
  • Innovate new techniques and conduct studies in optimizing ISP and performance for machineperception
Your Skills & Abilities (Required Qualifications)
  • BS, MS/ PhD in imaging science, EE, CS, or similar field with4+ years of hands-on experience in camera ISP tuning and evaluation
  • Must have hands-on experience tuningvarious ISP modules– AE, AWB, HDR processing, noise reduction and sharpness, tone mapping, and color tuning
  • Experience with different ISP architectures and camera development
  • Experience characterizing image sensors and tuning image sensor settings
  • Experience with at least one image quality evaluation software, preferably Imatest
  • Proficiency in programming languages like C/C++ or Python
  • EExperience in image processing and data analysis
What Will Give You a Competitive Edge (Preferred Qualifications)
  • Experience with automotive ISP tuning is a big plus
  • Exposure to firmware design and/or real-time systems
  • Experience with vendor management and manufacturing processes
  • Hands-on experience optimizing image sensor–level IQ settings and operating modes to balance noise, dynamic range, motion blur, and artifacts for ADAS/autonomous use cases.
  • Experience with optimizing camera ISP for computer vision algorithms or Machine Learning.
  • Experience evaluating how sensor hardware and optical design impact image quality and ISP tuning trade-offs.

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 located outside of New York, Colorado, California, or…

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