Principal ML Systems Engineer, Data Platform (Autonomous Vehicles)

General Motors•Austin, TX

1d•$233,400 - $339,650•Hybrid

About The Position

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]. We are seeking a highly skilled and experienced Principal ML Systems Engineer to join our Autonomous Vehicles team. In this role, you will own and to end data platform architecture across multiple teams, and play a critical part in designing, developing, and maintaining the robust data platforms essential for the development and deployment of self-driving car technology.

Requirements

BA or MS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field
10+ years in building distributed data platforms using major cloud providers and open-source frameworks
Expert-level proficiency in Java, C++, or Python, with a proven track record of designing and implementing robust, distributed systems.
Expertise in implementing Data Processing Frameworks (Beam, Spark) and serving layers optimized for high-throughput, low-latency delivery.
Experience optimizing services for cost efficiency, performance & reliability
Experience with Micro services architecture and proven ability to manage the full operational lifecycle of systems.
Deep understanding of full ML model lifecycle (feature engineering, training, validation, deployment, monitoring, etc.)
Strong passion, and understanding about self-driving technology and its potential impact on the world
Experience working with (100+) petabyte-scale ingestion, processing, and serving architectures.
Experience with SQL engines / queries

Nice To Haves

Master’s degree in Computer Science, Software Engineering, or related field
Building and optimizing large-scale cloud-native data platforms using GCP or similar cloud technologies.
Experience in self-driving, autonomous vehicle, ADAS, or connected vehicle data domains.
Ability to work cross-functionally with Data Science, ML, analytics, and product stakeholders to deliver production-ready data products.
Familiarity with robustness, validation, and simulation for ML systems used in autonomous driving contexts.

Responsibilities

Design & develop the next generation distributed ML data platform (Ingestion, Processing, Serving) using GCP and open-source frameworks.
Leading the strategy of building performant and efficient multi-cloud platforms
Collaborate with stakeholders (ML & Data Engineers), translate needs & pain points into requirements, build self-serve capabilities and drive adoption
Deliver e2e technical projects owning major technical decisions and tradeoffs & contribute to the team’s strategic roadmap.
Champion engineering & operational excellence by continuously improving systems and processes
Actively participate in team’s planning, code reviews and design discussions
Conduct technical interviews, onboard new and mentor junior engineers