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Principal ML Systems Engineer, Data Platform (Autonomous Vehicles)

  • Localização
    • Austin, Texas
    • Bellevue, Washington
  • Tipo de trabalho Full time
  • Postou
  • Job Requisition JR-202611152

Descrição

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

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.  

What You’ll Do

  • 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 

Your Skills & Abilities (Required Qualifications)

  • 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 

What Can Give You a Competitive Advantage (Preferred Qualifications)

  • 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.

This job may be eligible for relocation benefits.

Company Vehicle:

Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Compensation: 

  • The expected base compensation for this role is: $233,400 - $339,650. 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. 

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.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)

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Informações sobre diversidade

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Declaração de Igualdade de Oportunidades de Emprego (EUA)

A General Motors tem orgulho de ser um empregador que oferece oportunidades iguais.  Todos os candidatos qualificados serão considerados para o emprego, independentemente de raça, cor, religião, sexo, orientação sexual, identidade de gênero, origem nacional, deficiência ou status como veterano protegido. 

Adaptações (EUA e Canadá)

A General Motors oferece oportunidades a todos os candidatos a emprego, incluindo pessoas com deficiências. Se você precisa de uma adaptação razoável para ajudá-lo na sua pesquisa de cargos ou solicitação de emprego, fale conosco pelo e-mail [email protected] ou pelo telefone 800-865-7580. No seu e-mail, inclua uma descrição da adaptação específica que você está solicitando assim como o nome do cargo e o número de requisição do cargo ao qual está se candidatando.