Senior AI/ML Engineer, AV Pipelines & Lineage

The Role:  

As a Senior AI/ML Engineer, you will focus on designing and implementing scalable ML infrastructure solutions. You will take ownership of key technical projects, provide mentorship to junior engineers, and collaborate across teams to solve complex problems. This is an individual contributor role emphasizing deep technical impact rather than leadership of large teams. 

Note: This role is part of an ML infrastructure engineering team and does not involve applying machine learning models for specific tasks. The focus is on developing infrastructure products that empower GM teams to perform machine learning and data science at scale.  

What you’ll do  

• • Design & Implementation:  Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud. 

  • Project Ownership:  Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs. 

  • Collaboration:  Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts. 

  • Mentorship & Recruitment:  Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing. 

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Your Skills & Abilities (Required Qualifications)  

• • 5+ years of experience, with a strong background in large-scale distributed systems preferred. 

  • 1+ years of experience leading and driving large-scale initiatives. 

  • Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages. 

  • Experience working with relational and NoSQL databases. 

  • Demonstrated ability to develop and maintain systems at scale. 

  • A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience. 

  • A passion for autonomous vehicle technology and its transformative potential. 

  • Strong attention to detail and a commitment to accuracy. 

  • A proven track record of efficiently solving complex problems. 

  • A startup mentality with a willingness to embrace uncertainty and wear multiple hats. 

What Will Give You a Competitive Edge (Preferred Qualifications)  

• • Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services. 

  • Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc. 

  • Experience with Kubernetes. 

  • Understanding of Machine Learning (ML) models/pipelines. 

  • Python/C++/Golang proficiency. 

  • Relevant publications

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 $155,420 to $395,900. 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.  

Benefits:   

• 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.  

Relocation:  This job may be eligible for relocation benefits.  

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Mountain View, you are expected to report to that location three times a week, at minimum.