Sr. Machine Learning Engineer

Description

The Role

GM is developing the next generation of embedded platform software to deliver state-of-the-art ADAS features to our customers. We are looking for an expert Sr. Camera ISP Engineer to join our Autonomous Vehicle team 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, which is responsible for developing camera data pipelines for autonomous vehicles. You will interact with camera hardware engineers, embedded software engineers, systems engineers, Embodied AI engineers, technical program managers internally, and various external imager component vendors to 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) tuning optimized for 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 comprehensive objective and subjective image quality evaluations using lab charts and real-world scenes, selecting appropriate metrics and analyses for each, leveraging tools such as Imatest and 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, aligning objectives and success metrics across EAI, system, and sensor teams.

Work with sensor validation and vehicle fleet teams to perform ISP characterization, image quality tuning and evaluation, and troubleshoot image quality related issues

Collaborate with machine learning engineers and hardware teams to architect sensing strategy for autonomous vehicles at scale

Innovate new techniques and conduct studies in optimizing ISP and performance for machine perception

Your Skills & Abilities (Required Qualifications)

BS, MS/ PhD in imaging science, EE, CS, or similar field with 4+ years of hands-on experience in camera ISP tuning and evaluation

Must have hands-on experience tuning various 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

Experience 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 Washington

Compensation: The expected base compensation for this role is : $174,900 - $250,200 Actual base compensation within the identified range will vary based on factors relevant to the position.

Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays.

#LI-EL1

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

The selected candidate will be required to travel <25% for this role.

This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

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Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

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