Data & ML Infrastructure Architect - Remote

Overview

We’re seeking a Machine Learning & Data Infrastructure Architect to lead the technical vision and architecture for the systems that power our entire machine learning lifecycle—from data ingestion and storage to model training, evaluation, and deployment. This is a mission-critical leadership role within the ML & Data Platform team, shaping the infrastructure that supports terabytes of daily sensor data and petabyte-scale datasets essential for autonomous vehicle development.

In Short

• Own the architecture of Motional’s ML data infrastructure, enabling scalable ingestion, storage, curation, and access for 100+ engineers and researchers across autonomy teams.
• Design and evolve infrastructure to support petabyte-scale machine learning workflows, including multimodal perception data, synthetic data, simulation output, and continuous training pipelines.
• Architect high-throughput systems for distributed training on large GPU clusters, driving significant improvements in utilization, throughput, and job efficiency.
• Establish robust data governance, observability, and retention strategies to ensure compliance, reproducibility, and long-term data utility.
• Collaborate cross-functionally with ML engineers, autonomy researchers, data engineers, and DevOps to ensure tight integration between infrastructure and user workflows.
• Lead technical strategy and roadmap development for the ML & Data Platform team, incorporating cutting-edge tools and best practices from industry and open source.
• Mentor and influence engineers across teams, promoting engineering excellence in distributed systems, ML platforms, and autonomy-scale data management.

Requirements

• 15+ years of meaningful software engineering experience, including significant architecture-level ownership in ML, data infrastructure, or high-scale systems.
• Proven experience leading the design of ML platforms that serve large-scale training and inference workloads.
• Deep technical fluency in distributed storage, high-volume data pipelines, and data compression strategies for ML use cases.
• Strong knowledge of Linux systems, Python, and C++ or similar performance-oriented languages.
• Experience operating in hybrid environments: bare metal, HPC, and public cloud (AWS/GCP/Azure).
• Comfortable owning cross-org initiatives and influencing system-level design across autonomy, simulation, and platform teams.
• Prior work in robotics, autonomous vehicles, or safety-critical domains strongly preferred.

Benefits

• Motional’s benefits include medical, dental, vision, 401k with a company match, health saving accounts, life insurance, and pet insurance.