Staff ML Systems Engineer

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 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 across multiple teams 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

• 10+ years working with big data
• Bachelor's in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real-world experience
• Experience building PB scale ML data management systems (datalake, data warehouse) 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
• Startup mentality - openness to dealing with unknown unknowns and wearing many hats

• MS or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field
• 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

• The expected base compensation for this role is: $165,000 - $298,800. 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.