Staff AI/ML Engineer, Future Sensing, Embodied AI

General Motors (GM)

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Sunnyvale, CA
Salary
$189,300–$320,700 / yr
Posted
100 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $220k
This role $255k
$158k most similar roles pay here $338k

This role pays more than 79% of similar roles. Most pay $184,574–$254,750 — the shaded band above. At the midpoint, this role pays about $255k versus about $220k for comparable roles.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

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At a glance

TL;DR · Staff AI/ML Engineer, Future Sensing, Embodied AI

Staff AI/ML Engineer - Future Sensing, Embodied AI joins the Embodied AI team to develop and deploy machine learning solutions supporting safe, reliable autonomous vehicle behavior across real-world scenarios. As a senior individual contributor, you will drive end-to-end technical work regarding sensing architecture, multi-modal sensor fusion using cameras, lidar, and radar, and system integration. You will design perception models for detection, tracking, and localization while developing infrastructure for large-scale data processing and model training. The role requires expertise in PyTorch, Python, NumPy, Pandas, and Apache Spark to build scalable onboard solutions. You will translate complex architecture questions into technical evidence for sensor and compute decisions while mentoring engineers through code reviews. This position addresses the critical challenge of creating robust perception pipelines that function under adverse weather, noise, and various environmental constraints.

What you'll do

  • Design and implement AI/ML solutions for autonomous driving and future sensing architectures.
  • Lead technical studies regarding sensor selection, configuration, placement, and multi-modal sensor fusion.
  • Architect perception models and pipelines for detection, tracking, localization, and uncertainty estimation.
  • Define robust model-level and system-level metrics to evaluate performance across different sensor configurations.
  • Manage the full model development lifecycle including data curation, training, validation, and deployment optimization.
  • Collaborate with simulation teams to define requirements for synthetic data and sensor models in adverse conditions.
  • Translate complex architectural questions into concrete experiments and technical go/no-go evidence packages.
  • Build infrastructure and tools to support large-scale data processing and rapid model iteration.

What we're looking for

  • Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field.
  • Strong experience building and scaling AI/ML systems for perception, autonomy, robotics, or other real-world systems.
  • Deep hands-on experience with PyTorch and strong proficiency in Python.
  • Experience with model training pipelines, large-scale data workflows, and infrastructure for efficient model iteration.
  • Proficiency in data processing using tools such as NumPy, Pandas, and Apache Spark.
  • Strong experience with multi-modal sensor fusion and perception pipelines using cameras, radar, lidar, or related modalities.
  • Experience with model validation, debugging, performance optimization, and error analysis under real-world constraints.
  • Experience deploying ML models for production environments and understanding end-to-end deployment workflows.

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