Senior Engineering Manager - Scalable Machine Learning

Description

The company is building a fully in-house hands-free driver assistance platform, set to debut in 2027 on an all-new model from its parent automaker, with the goal of making trips safer, less stressful and more enjoyable for millions of customers.

The company operates independently as a subsidiary of an automaker and moves at startup speed. Its headquarters is in Pittsburgh, with engineering centers in Dearborn, Michigan and Palo Alto, California.

You would work alongside specialists in machine learning, robotics, cloud platforms, mapping, sensors and compute, test operations, and systems and safety engineering.

The Intelligent Systems team turns raw sensor input into understanding, mainly through computer vision and machine learning. It owns all downstream processing for the onboard sensor suite and the full cloud infrastructure for machine learning.

The Scalable ML team builds the data generation, orchestration and distributed training infrastructure that lets ML developers work with large data volumes. It works across the ML Platform, Jobs Platform, Cloud Platform and High Performance Computing teams.

The role combines running a high-performing engineering team with acting as the technical bridge to organizations that do not report to you.

Responsibilities

• Lead and mentor a team of software engineers, setting high technical standards and supporting their ongoing skill growth in scalable machine learning infrastructure.
• Own a multi-quarter technical strategy for data generation, orchestration and distributed training, including how it depends on and shapes other teams' roadmaps.
• Set the technical direction for how the team's data and training infrastructure works with the adjacent platform teams.
• Represent the team in org-wide planning and architecture decisions, settling cross-team tradeoffs on shared resources such as GPU scheduling and quota, job orchestration, storage and compute cost.
• Lead the adoption of advanced MLOps practices, including model artifact management, experiment tracking, and automated deployment and testing, at a standard other teams follow.
• Build lasting working relationships with peer managers and architects on the ML Platform, Jobs Platform, Cloud Platform and HPC teams, reviewing shared infrastructure changes together.
• Hold the team's systems to a high reliability bar, including root-causing, fixing and preventing incidents that cross team boundaries.

Requirements

• A Bachelor's degree and 10 years of experience, or a Master's degree and 8 years, in computer engineering, computer science, electrical engineering, robotics or a related field.
• At least 10 years of software development experience, including at least 5 years in a Staff or Principal engineering or senior technical leadership role.
• You have set technical strategy and direction across several teams or organizations, not only within a single team.
• Extensive experience designing, building and running large-scale distributed systems and cloud infrastructure for machine learning, including cross-team dependencies from shared compute such as GPU scheduling and quota, job orchestration and multi-tenant clusters.
• Proven skill building and optimizing machine learning data pipelines, covering data generation, management and distributed training.
• Strong Python skills for building high-performance, production-quality software.
• You influence and align peer teams and leaders without direct authority over them.
• You have delivered complex multi-org software projects from concept to production, with a focus on scalability, reliability and organizational alignment.
• A Master's or PhD in computer science, electrical engineering, robotics or a field closely tied to them.
• Hands-on experience with distributed machine learning frameworks and tools such as Ray, PyTorch, Dagster, LakeFS or PyArrow.
• Experience with multi-sensor data fusion and processing techniques relevant to autonomous driving.
• Familiarity with safety-critical software development principles in automotive or robotics.
• Deep understanding of machine learning concepts, computer vision use cases and the challenges of L2/L3 autonomy.

Conditions

This is a full-time position. The expected base salary range in California is $253,120 to $379,680 USD. Starting pay depends on factors including exact work location, experience, relevant training and education, and skill level.

You must be legally authorized to work in the United States on a permanent basis. Employment eligibility must be verified at hire. Visa sponsorship is available for this position.

Benefits

• Competitive pay packages.
• Medical, dental and vision insurance for you and your family.
• Health savings account, with an employer match where available.
• 401(k) retirement plan with an employer match that vests immediately.
• Group term life insurance paid by the employer, plus the option to buy voluntary life cover.
• Paid parental leave and an adoption and surrogacy support program.
• Paid medical leave.
• Unlimited vacation time, plus 15 paid holidays.
• Daily lunches, snacks and drinks at all office locations.
• Pre-tax accounts for healthcare and dependent care costs, and pre-tax commuter benefits.
• Monthly wellness stipend.
• Backup child and elder care.
• Reimbursement for professional development.
• Employee assistance program.
• Discounts on legal services, identity theft protection, pet insurance and more.
• Employee resource groups, a quarterly team activity stipend and wellness initiatives.
• Eligibility for annual bonus programs and equity compensation, subject to eligibility requirements.