Data & ML infrastructure architect

Overview

Remote

$205 - $280

Full Time

Skills

Data

Machine learning

infrastructure

architect

Job Details

Position Title: Data & ML Infrastructure Architect

Location: Remote (USA)
Job Type: Direct Hire
Salary Range: $205,000 $282,000/year
Company: Protingent Staffing (in partnership with Motional)

About the Role:

Protingent has an exciting opportunity for a Data & ML Infrastructure Architect to join a pioneering team at a global leader in autonomous vehicle (AV) technology. This is a mission-critical leadership position where you'll own the architectural vision for the systems powering the entire machine learning lifecycle from data ingestion and curation to training, evaluation, and deployment.

Key Responsibilities:

Architect Scalable ML Infrastructure: Lead the design of systems for ingestion, storage, curation, and access of large-scale multimodal datasets, used by over 100 engineers and researchers.
Support Petabyte-Scale Workflows: Build infrastructure capable of handling simulation outputs, synthetic data, and sensor logs essential for AV development.
Optimize Distributed Training: Architect high-throughput systems on GPU clusters, enhancing training efficiency, job throughput, and utilization.
Enable Data Governance & Observability: Implement robust governance, compliance, and monitoring strategies to ensure reproducibility and long-term utility.
Cross-Functional Collaboration: Work closely with ML engineers, autonomy researchers, data engineers, and DevOps to integrate infrastructure seamlessly into the workflow.
Strategic Leadership: Define and drive the ML & Data Platform roadmap, staying aligned with industry innovations and open-source advancements.
Mentor and Influence: Provide technical leadership across teams, fostering engineering best practices in distributed systems and ML infrastructure.

Required Qualifications:

15+ years of hands-on software engineering experience, including architectural leadership in ML systems, data infrastructure, or scalable backend systems.
Proven track record building ML platforms that support high-scale training and inference workflows.
Deep expertise in:
- Distributed storage and compute
- High-throughput data pipelines
- Data compression for ML applications
Strong coding skills in Python and C++ (or similar performance-oriented languages).
Advanced Linux systems knowledge.
Experience operating across bare metal, HPC, and cloud platforms (AWS, Google Cloud Platform, or Azure).
Demonstrated success influencing systems across autonomy, simulation, and infrastructure teams.
Prior experience in robotics, autonomous vehicles, or safety-critical domains preferred.

Preferred Qualifications:

Infrastructure leadership experience at a top-tier ML/AI or AV company.
Open-source contributor to ML or data infrastructure projects.
Familiarity with ML experiment tracking, versioned datasets, and model evaluation systems.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.