General Motors
Staff Machine Learning Engineer
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 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. The ML Orchestration team at GM builds and maintains the foundational infrastructure that powers ML workflows across the company. Our core responsibility is the development and evolution of Roboflow, GMs in-house semantic orchestration platform designed to streamline and scale complex ML pipelines, from experimentation to production. A key pillar of our work is AI Lineage our capability to track, visualize, and understand the entire lifecycle of ML artifacts. This includes tracing the origin of data, model training runs, hyperparameters, code versions, and evaluation metrics. AI Lineage provides transparency, auditability, and reproducibility across our ML systems, which is essential for debugging, model governance, regulatory compliance, and improving long-term model quality. Together, Roboflow and AI Lineage help our engineers move faster with higher confidence, enabling GM to iterate quickly while maintaining the safety and performance standards required for autonomous vehicle development. We are seeking an experienced Staff Machine Learning Engineer to drive key initiatives within our ML Orchestration team. In this role, you will be instrumental in scaling our internal ML platform, building automation and self-service tools, and ensuring the reliability and efficiency of large-scale ML pipelines across GM. A major focus area for this role is the development and evolution of AI Lineage our system for capturing, querying, and visualizing the full lifecycle of machine learning artifacts. You will help design lineage tracking for data transformations, model training, evaluation runs, and pipeline dependencies. This functionality is critical for enabling transparency, reproducibility, debugging, and regulatory compliance across our ML ecosystem. What You'll Be Doing Design & Implementation: Architect, implement, and test scalable, cloud-native distributed systems using modern cloud platforms such as Google Cloud Platform (GCP) or Microsoft Azure. Build robust infrastructure to support large-scale ML workflows and data processing at GM. Project Ownership: Lead technical projects end-to-endfrom early design through production deployment. Shape the product roadmap and drive key architectural decisions, balancing performance, reliability, and long-term maintainability. Cross-Team Collaboration: Actively participate in design reviews, team planning, and code reviews. Collaborate across multiple engineering teams to deliver cohesive platform solutions. Anticipate integration points and proactively manage dependencies and trade-offs. Mentorship & Recruiting: Foster a culture of technical excellence and growth. Interview candidates using calibrated evaluation criteria, onboard new hires, and mentor engineers and interns to help them grow technically and professionally. Minimum Qualifications
8+ years of industry experience, with a strong focus on large-scale distributed systems or cloud infrastructure. 3+ years of experience leading and delivering complex technical initiatives across teams. Strong programming skills in Python, C++, Go, or similar languages, with demonstrated experience building production-grade systems. Hands-on experience working with relational and NoSQL databases. Proven ability to design, build, and maintain highly scalable systems in production environments. Bachelors, Masters, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related fieldor equivalent practical experience. Deep attention to detail, strong problem-solving skills, and a track record of building high-quality systems. Passion for autonomous vehicles, infrastructure engineering, and advancing the state of ML platforms. Adaptability and a startup mindsetcomfortable working in ambiguity and stepping outside your core responsibilities when needed. Preferred Qualifications
Experience with GCP, Azure, or AWS cloud platforms. Familiarity with open-source ML orchestration tools such as Kubeflow, Flyte, Airflow, or similar platforms. Experience with Kubernetes and container orchestration at scale. Understanding of ML pipelines, data lineage, model lifecycle management, and reproducibility challenges in machine learning systems. Strong proficiency in one or more of Python, C++, or Golang. Contributions to open-source projects or relevant technical publications. If you're excited to tackle some of today's most complex ML Infra engineering challenges, see the impact of your work in real-world AV applications, and help shape the future of AI infrastructure at GMthis is the team for you. 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. 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. An incentive pay program offers payouts based on company performance, job level, and individual performance. 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. 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-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources.
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 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. The ML Orchestration team at GM builds and maintains the foundational infrastructure that powers ML workflows across the company. Our core responsibility is the development and evolution of Roboflow, GMs in-house semantic orchestration platform designed to streamline and scale complex ML pipelines, from experimentation to production. A key pillar of our work is AI Lineage our capability to track, visualize, and understand the entire lifecycle of ML artifacts. This includes tracing the origin of data, model training runs, hyperparameters, code versions, and evaluation metrics. AI Lineage provides transparency, auditability, and reproducibility across our ML systems, which is essential for debugging, model governance, regulatory compliance, and improving long-term model quality. Together, Roboflow and AI Lineage help our engineers move faster with higher confidence, enabling GM to iterate quickly while maintaining the safety and performance standards required for autonomous vehicle development. We are seeking an experienced Staff Machine Learning Engineer to drive key initiatives within our ML Orchestration team. In this role, you will be instrumental in scaling our internal ML platform, building automation and self-service tools, and ensuring the reliability and efficiency of large-scale ML pipelines across GM. A major focus area for this role is the development and evolution of AI Lineage our system for capturing, querying, and visualizing the full lifecycle of machine learning artifacts. You will help design lineage tracking for data transformations, model training, evaluation runs, and pipeline dependencies. This functionality is critical for enabling transparency, reproducibility, debugging, and regulatory compliance across our ML ecosystem. What You'll Be Doing Design & Implementation: Architect, implement, and test scalable, cloud-native distributed systems using modern cloud platforms such as Google Cloud Platform (GCP) or Microsoft Azure. Build robust infrastructure to support large-scale ML workflows and data processing at GM. Project Ownership: Lead technical projects end-to-endfrom early design through production deployment. Shape the product roadmap and drive key architectural decisions, balancing performance, reliability, and long-term maintainability. Cross-Team Collaboration: Actively participate in design reviews, team planning, and code reviews. Collaborate across multiple engineering teams to deliver cohesive platform solutions. Anticipate integration points and proactively manage dependencies and trade-offs. Mentorship & Recruiting: Foster a culture of technical excellence and growth. Interview candidates using calibrated evaluation criteria, onboard new hires, and mentor engineers and interns to help them grow technically and professionally. Minimum Qualifications
8+ years of industry experience, with a strong focus on large-scale distributed systems or cloud infrastructure. 3+ years of experience leading and delivering complex technical initiatives across teams. Strong programming skills in Python, C++, Go, or similar languages, with demonstrated experience building production-grade systems. Hands-on experience working with relational and NoSQL databases. Proven ability to design, build, and maintain highly scalable systems in production environments. Bachelors, Masters, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related fieldor equivalent practical experience. Deep attention to detail, strong problem-solving skills, and a track record of building high-quality systems. Passion for autonomous vehicles, infrastructure engineering, and advancing the state of ML platforms. Adaptability and a startup mindsetcomfortable working in ambiguity and stepping outside your core responsibilities when needed. Preferred Qualifications
Experience with GCP, Azure, or AWS cloud platforms. Familiarity with open-source ML orchestration tools such as Kubeflow, Flyte, Airflow, or similar platforms. Experience with Kubernetes and container orchestration at scale. Understanding of ML pipelines, data lineage, model lifecycle management, and reproducibility challenges in machine learning systems. Strong proficiency in one or more of Python, C++, or Golang. Contributions to open-source projects or relevant technical publications. If you're excited to tackle some of today's most complex ML Infra engineering challenges, see the impact of your work in real-world AV applications, and help shape the future of AI infrastructure at GMthis is the team for you. 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. 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. An incentive pay program offers payouts based on company performance, job level, and individual performance. 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. 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-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources.