layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Senior ML Infrastructure Engineer - Embodied AI Scaling Foundations at General Motors | LAYIQ

Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM.
Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality.
Take a holistic view of projects, considering their impact across multiple teams, and proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build.
Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting. Mentor and onboard junior engineers and interns, helping them grow their careers.
Your Skills & Abilities (Required Qualifications)
3+ years of experience building large-scale distributed systems/applications or advanced ML Applications.
Proven track record of building robust frameworks with high-quality, long-lasting APIs.
Deep understanding and practical experience with machine learning algorithms.
Expertise in building reliable, highly performant, and cost-efficient systems leveraging modern cloud infrastructure.
Hands-on experience with the entire ML development lifecycle and MLOps practices.
Demonstrated ability to collaborate effectively across multiple teams and organizations.
Proficiency working with containerization and orchestration technologies (Docker, Kubernetes).
A strong passion for self-driving technology and its transformative potential.
Exceptional coding skills in Python or C++.
BS, MS, or PhD in Computer Science, Math, or equivalent practical experience.
Exceptional candidates may also have: Experience with distributed training methodologies.
A background in optimizing model training performance.
Experience scaling model training across large clusters of GPUs/CPUs or other accelerators.
Familiarity with deep learning frameworks such as PyTorch, TensorFlow, etc.
A strong grasp of performance profiling and state-of-the-art training optimization algorithms, including their performance characteristics and effect on model convergence.
Experience with advanced build systems (Bazel, Buck, Blaze, or Cmake).
3+ years of professional experience
Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of an office, you are expected to report to that location three times a week, at minimum.
Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be r epresentative for positions located outside of the California Bay Area.

Senior ML Infrastructure Engineer - Embodied AI Scaling Foundations

Employer job description

About the team:

What you'll do:

Benefits:

Why Join Us

Benefits Overview

About this listing