Staff Machine Learning Engineer – ML Training Infrastructure

About This Opportunity

We are representing a confidential automotive technology organization in their search for a Staff Machine Learning Engineer - ML Training Infrastructure. Our client is building advanced AI systems that power the next generation of intelligent vehicle capabilities, and they need a technical leader who can architect and scale their ML training platform to support cutting-edge research and development.

In this staff-level role, you'll define technical direction, drive architecture decisions, and build scalable infrastructure that enables distributed training of large-scale models. You'll work across teams to shape platform strategy, optimize performance across heterogeneous compute environments, and elevate engineering standards organization-wide.

This is a remote position within the United States, with occasional travel to Sunnyvale, CA as needed.

Responsibilities

• Define and drive the architecture, design, and development of scalable ML frameworks and platform capabilities to support model training at scale
• Lead model training performance analysis and optimization efforts across distributed training workflows, improving scalability, efficiency, and cost
• Raise the bar on system observability, debuggability, operational excellence, and developer experience across the ML training stack
• Own large, ambiguous, cross-functional technical initiatives from strategy through execution, including technical roadmap definition and tradeoff analysis
• Influence platform direction by identifying long-term infrastructure investments, setting engineering standards, and driving adoption of best practices
• Collaborate across organizational boundaries to align requirements, resolve technical disagreements, and integrate new capabilities into the platform ecosystem
• Mentor engineers through design reviews, technical guidance, and hands-on partnership

What We're Looking For

Required Qualifications:

• Bachelor's degree or higher in Computer Science or a related field, or equivalent practical experience
• 7+ years of professional software engineering experience
• 5+ years of specialized experience in AI/ML infrastructure, particularly enabling distributed training for large-scale ML models
• Strong programming skills in Python, with deep proficiency in PyTorch (preferred), TensorFlow, or similar ML systems
• Proven experience designing and operating distributed systems for ML training, including distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure)
• Demonstrated track record of leading technically ambiguous, cross-team infrastructure initiatives and driving them to measurable impact
• Strong architectural judgment and ability to make sound technical tradeoffs across performance, reliability, usability, and cost
• Willingness to travel to Sunnyvale, CA as needed
• Comfortable operating in highly ambiguous and dynamic environments

Preferred Qualifications:

• Deep expertise in PyTorch 2.x+ and distributed training frameworks
• Experience designing and developing training platforms that support FSDP, pipeline parallelism, and other scalable solutions for training large foundational models
• Experience profiling, analyzing, debugging, and optimizing training and data loading performance at scale
• Strong record of technical leadership through architecture reviews, roadmap influence, and cross-team execution
• Excellent communication skills, with the ability to build consensus, navigate controversial decisions, and provide constructive technical feedback
• Self-motivated, execution-oriented, and driven by delivering broad organizational impact

How We Work With You

When you apply through Get A Job.ai, our talent team will review your background and conduct an initial screening to understand your experience and career goals. If there's a strong match, we'll submit your profile to our client for consideration. Please note that you should not contact the client directly—we'll manage all communication and coordination throughout the interview process.

Our recruiters are here to support you at every stage, from initial conversations through offer negotiation, ensuring you have the guidance and advocacy you need.

Pay

Compensation details will be discussed during the screening process and are based on experience, qualifications, and our client's approved ranges for this position.

Equal Employment Opportunity: Get A Job.ai is committed to providing equal employment opportunities to all applicants regardless of race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, veteran status, or any other protected characteristic under applicable law.