Staff ML Engineer, Inference Platform

  • Mountain View, CA
  • Posted 12 hours ago | Updated moments ago

Overview

On Site
Hybrid
USD 177,000.00 - 270,900.00 per year
Full Time

Skills

Reporting
MI
Marketing Intelligence
Network Layer
Innovation
Use Cases
Concurrent Computing
Scalability
GPU
Data Mining
Roadmaps
User Experience
Real-time
Conflict Resolution
Problem Solving
Usability
Collaboration
Decision-making
Orchestration
Caching
Optimization
Research
Art
Distributed Computing
IT Management
Python
C++
Communication
Cloud Computing
Google Cloud
Google Cloud Platform
Microsoft Azure
Amazon Web Services
Multitasking
Interfaces
Workflow
Data Processing
Computer Hardware
Open Source
Machine Learning (ML)
AV
Audiovisual
Artificial Intelligence
FOCUS
SAP BASIS
Recruiting
Screening

Job Details

Job Description

Hybrid This role is categorized as hybrid. This means the successful candidate is expected to report to the GM Global Technical Center - Cole Engineering Center Podium , MI or Mountain View Technical Center , CA at least three times per week, at minimum or other frequency dictated by the business. This job is eligible for relocation assistance.

About the Team:

The ML Inference Platform is part of the AI Compute Platforms organization within Infrastructure Platforms. Our team owns the cloud-agnostic, reliable, and cost-efficient platform that powers GM's AI efforts. We're proud to serve as the AI infrastructure platform for teams developing autonomous vehicles (L3/L4/L5), as well as other groups building AI-driven products for GM and its customers.

We enable rapid innovation and feature development by optimizing for high-priority, ML-centric use cases. Our platform supports the serving of state-of-the-art (SOTA) machine learning models for experimental and bulk inference, with a focus on performance, availability, concurrency, and scalability. We're committed to maximizing GPU utilization across platforms (B200, H100, A100, and more) while maintaining reliability and cost efficiency.

About the Role:

We are seeking a Staff ML Infrastructure engineer to help build and scale robust Compute platforms for ML workflows. In this role, you'll work closely with ML engineers and researchers to ensure efficient model serving and inference in production, for their workflows such as data mining, labeling, model distillation, simulations and more. This is a high-impact opportunity to influence the future of AI infrastructure at GM.

You will play a key role in shaping the architecture, roadmap and user-experience of a robust ML inference service supporting real-time, batch, and experimental inference needs. The ideal candidate brings experience in designing distributed systems for ML, strong problem-solving skills, and a product mindset focused on platform usability and reliability.

What you'll be doing:
  • Design and implement core platform backend software components.
  • Collaborate with ML engineers and researchers to understand critical workflows, parse them to platform requirements, and deliver incremental value.
  • Lead technical decision-making on model serving strategies, orchestration, caching, model versioning, and auto-scaling mechanisms.
  • Drive the development of monitoring, observability, and metrics to ensure reliability, performance, and resource optimization of inference services.
  • Proactively research and integrate state-of-the-art model serving frameworks, hardware accelerators, and distributed computing techniques.
  • Lead large-scale technical initiatives across GM's ML ecosystem.
  • Raise the engineering bar through technical leadership, establishing best practices.
  • Contribute to open source projects; represent GM in relevant communities.

Additional Job Description

Minimum Requirements
  • 8+ years of industry experience, with focus on machine learning systems or high performance backend services.
  • Expertise in either Go, Python, C++ or other relevant coding languages.
  • Expertise in ML inference, model serving frameworks (triton, rayserve, vLLM etc).
  • Strong communication skills and a proven ability to drive cross-functional initiatives.
  • Experience working with cloud platforms such as Google Cloud Platform, Azure, or AWS.
  • Ability to thrive in a dynamic, multi-tasking environment with ever-evolving priorities.


Preferred Qualifications
  • Hands-on experience building ML infrastructure platforms for model serving/inference.
  • Experience working with or designing interfaces, apis and clients for ML workflows.
  • Experience with Ray framework, and/or vLLM.
  • Experience with distributed systems, and handling large-scale data processing.
  • Familiarity with telemetry, and other feedback loops to inform product improvements.
  • Familiarity with hardware acceleration (GPUs) and optimizations for inference workloads.
  • Contributions to open-source ML serving frameworks.


Why Join Us?

If you're excited to tackle some of today's most complex engineering challenges, see the impact of your work in real-world AV applications, and help shape the future of AI infrastructure at GM-this is the team for you.

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 : $177,000 - $270,900 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.

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.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources .

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 .

Accommodations

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