Principal Engineer, Data & ML Infrastructure

Mission Summary:

We are seeking a highly skilled and motivated Principal Engineer for our large-scale autonomous vehicle evaluation framework. The ideal candidate will have a strong background in cloud infrastructure, distributed systems and technical leadership, with experience in developing and deploying advanced large-scale orchestration frameworks to support simulation and evaluation workloads.

At Motional, large-scale orchestration for simulation, evaluation, and data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of engineers and deployed multiple times a day. The Ground Truth Regression team provides a large-scale perception analysis framework for validating all changes to perception that can impact the autonomous vehicle behavior.

The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis, and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UI’s.

What You'll Do:

• Drive innovation by researching and developing new large-scale data warehousing frameworks.
• Maintain and scale a large-scale orchestration framework with a focus on reliability, fault tolerance, and cost efficiency.
• Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software.
• Provide technical leadership by setting architectural direction, driving engineering best practices, and mentoring engineers through design and code reviews
• Manage project timelines, resources, and deliverables to ensure successful project execution.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Excellent communication and problem-solving skills.
• Proficiency in Go (Golang) and Python for building high-performance, concurrent microservices and platform tooling
• Deep hands-on experience building production infrastructure on public clouds (AWS, GCP, or Azure) and managing containerized workloads at scale using Kubernetes (K8s).
• Experience with large-scale data processing and distributed computing technologies.

Bonus Points:

• Ph.D. in Computer Science or a related field.
• Knowledge of or hands-on experience with OLAP databases (e.g., ClickHouse) for data analysis.
• Experience with machine learning in the autonomous driving domain.
• Hands-on experience architecting large-scale orchestration platforms that run multi-thousand GPU/CPU workloads reliably and cost-efficiently.
• Experience in machine learning, data mining, and statistical analysis.

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Salary Range