Staff AI/ML Engineer - CI Platform

Staff Engineer

This role is categorized as hybrid. This means the selected candidate is expected to report to the office in Austin, Detroit, Warren, Milford, Mountain View or Sunnyvale a minimum of 3 days per week. This position can be considered Remote if the successful candidate is in the Seattle, Washington area.

The selected candidate will be required to travel less than 25% for this role. This job may be eligible for relocation benefits.

About Us

The AI Cloud and Developer Infrastructure organization is responsible for delivering and maintaining the tools and services engineers here at GM use every day to do their best work and drive our cars forward. Tools and services we work on enhancing the entire development process of engineers at GM — how/where code is checked out, modified, compiled, tested, merged, and eventually deployed. Our goal is to ensure our AV engineers and others here have world class tools and a seamless development experience so that they can focus on the problems that matter most in their domain.

The Role

We are looking for a Staff Engineer with an extensive engineering background, experience using a variety of developer tools and technologies, and who is passionate about developer productivity. As a leader on this team, we are looking for someone who cares deeply about the technical development of other engineers on the team and can effectively balance the needs and priorities of the business, our users, and the growth of our engineers.

The way this engineer will deliver impact may vary depending on the situation, but they will be expected to be able to identify how they can best have impact with minimal guidance.

The Team

The Continuous Integration (CI) Platform team owns our CI infrastructure along with the tools that improve the CI customer experience. We are part of the AI and Cloud Developer Productivity Organization and own the building blocks to produce high quality CI experiences and workflows. This includes services such as the Remote Build Execution (RBE) service which allows GM AI to reliably test at scale and the build artifact storage which is a FUSE based network file system used in conjunction with RBE. Our goal is to accelerate AV development by supporting developer workflows for building, testing, and releasing software.

What You'll Do (Responsibilities)

• Identify engineering pain points and propose/design/implement solutions that are reliable, scalable, and maintainable
• Influence the team's technical roadmap
• Evaluate new tools and technologies through PoCs
• Ship improvements to our AV development toolchains and services which have a measurable and direct impact on engineering productivity and our core company metrics
• Drive software engineering best practices within your team, and create tooling which encourages these
• Help steer the engineering culture on the team
• Guide the team to find the right balance between delivering impact and addressing technical debt
• Mentor and grow engineers on the team
• Set the example for high levels of accountability
• Execute and deliver impact both individually and through the team
• Set strong boundaries when selecting external requests and pushing back on requests that do not align with our team vision

Minimum Qualifications (Must-Have)

• 7+ years of experience designing, building and operating production systems at scale in the cloud
• Bachelors Degree in Computer Science or related field or equivalent work experience
• Experience designing highly scalable, reliable, and maintainable services
• Experience writing in Go, Python, or other languages at production scale
• Understanding of Unix/Linux, SSH, and networking fundamentals
• Attention to detail, and a desire to improve processes and systems around you
• Ability to lead and influence others, both internal and external to the team
• Ability to research, document, communicate, and defend proposals, and provide and take critical feedback
• Ability to effectively make trade-offs and communicate the reasoning
• Ability to manage competing priorities, focus on shipping, and work effectively under pressure
• Passion for mentoring and growing junior engineers
• Passion for self-driving technology and its potential impact on the world

Preferred Qualifications (Nice-to-Have)

• Experience working with GCP
• Experience working with Docker and Kubernetes
• Experience owning or contributing to Open-Source projects

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.

• The salary range for this role: is $170,000 to $300,000. The actual base salary a successful candidate will be offered within this 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, tuition assistance programs, employee assistance program, GM vehicle discounts and more.