Remote Data & ML Infrastructure Architect

Description:

• We are seeking a Machine Learning & Data Infrastructure Architect to lead the technical vision and architecture for 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.
• The role is ideal for a senior technologist with a deep background in ML systems and data architecture, who thrives on building for scale, performance, and engineering excellence.
• Responsibilities include owning the architecture of Motional’s ML data infrastructure, enabling scalable ingestion, storage, curation, and access for over 100 engineers and researchers across autonomy teams.
• You will design and evolve infrastructure to support petabyte-scale machine learning workflows, including multimodal perception data, synthetic data, simulation output, and continuous training pipelines.
• The role involves architecting high-throughput systems for distributed training on large GPU clusters, driving significant improvements in utilization, throughput, and job efficiency.
• You will establish robust data governance, observability, and retention strategies to ensure compliance, reproducibility, and long-term data utility.
• Collaboration is key, as you will work cross-functionally with ML engineers, autonomy researchers, data engineers, and DevOps to ensure tight integration between infrastructure and user workflows.
• You will lead technical strategy and roadmap development for the ML & Data Platform team, incorporating cutting-edge tools and best practices from industry and open source.
• Mentoring and influencing engineers across teams to promote engineering excellence in distributed systems, ML platforms, and autonomy-scale data management is also part of the role.

Requirements:

• Candidates must have 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 is required.
• A deep technical fluency in distributed storage, high-volume data pipelines, and data compression strategies for ML use cases is essential.
• Strong knowledge of Linux systems, Python, and C++ or similar performance-oriented languages is necessary.
• Experience operating in hybrid environments, including bare metal, HPC, and public cloud (AWS/GCP/Azure), is required.
• Candidates should be comfortable owning cross-organizational initiatives and influencing system-level design across autonomy, simulation, and platform teams.
• Prior work in robotics, autonomous vehicles, or safety-critical domains is strongly preferred.

Benefits:

• The salary range for this role is estimated between $205,000 - $282,000 USD, based on various compensation factors including skills, experience, and role location.
• Additional forms of compensation may include bonuses or company equity.
• Motional offers a benefits program that includes medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.
• Candidates will receive more information about specific compensation and benefit details during the hiring process.