Description

This role is categorized as hybrid. This means the successful candidate is expected to report to offices in Austin, TX, Mountain View, CA or the Greater Seattle Area three times per week, at minimum [or other frequency dictated by the business if more than 3 days].

The Role

As an engineer on this team, you will be responsible for building and supporting a petabyte-scale data platform in the cloud and providing powerful foundations for GM ML Data Platform tools, frameworks, and services. Responsibilities include ensuring scalable, transparent, and reliable data ingestion and management; development of fast, robust, and spike-resistant data consumption, data mining, and processing tools for the entire company; and development of orchestration for large-scale post-processing, and computational pipelines.

What You’ll Do

• Lead us in the development, optimization and productionization of the next generation ML data processing platform using Beam and Spark in the cloud.
• Build self-serve capabilities to help customers to adopt the next generation ML data processing and mining platform
• Use the latest cloud technologies to own, design, implement, and test scalable distributed data systems in the cloud. Champion engineering excellence by continuously improving systems and processes
• Own technical projects from start to finish, contribute to the team’s product roadmap, and be responsible for major technical decisions and tradeoffs. Effectively participate in team’s planning, code reviews and design discussions
• Consider the effects of projects and proactively manage conflicts. Work together with partner teams and orgs to achieve cross-organizational goals and satisfy broad requirements
• Conduct technical interviews with well-calibrated standards and play an essential role in recruiting activities. Effectively onboard and mentor junior engineers and/or interns

Your Skills & Abilities (Required Qualifications)

• 7+ years of experience
• Experience in working with big data
• BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real-world experience
• Experience building ML data processing systems using Beam / Spark and its ecosystems from the ground up.
• Experience optimizing those data processing clusters for cost efficiency and performance
• Experience building serving systems capable of delivering data at high-throughput, low-latency and high QPS in a cost-efficient and spike-resilient manner.
• Experience building full ML model lifecycle solutions - from feature engineering to  training, validation, deployment and monitoring.
• Experience building scalable infrastructure on the cloud with Python or Java/Scala (or similar)
• Passionate about self-driving technology and its potential impact on the world
• Attention to detail and a passion for seeking truth
• A track record of efficiently solving complex problems

What Can Give You a Competitive Advantage (Preferred Qualifications)

• Demonstrable expertise in a building end-to-end data ingestion, processing and serving systems at petabyte scale from the ground up
• Proficiency in writing SQL queries for analytic purposes
• Relevant publications

This job may be eligible for relocation benefits.

Compensation: 

• The expected base compensation for this role is: $134,000 - $241,900. 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. 

• 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. 

#LI-CC1

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.

Total Rewards | 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

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us Careers.Accommodations@GM.com or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.