Staff Machine Learning Engineer - Perception
About this role
Traditional industries like food production, mining, and transport rely on physical operations that remain inefficient and constrained, and Atoms solves this problem by building Physical AI systems that understand, predict, and control the real world. As a foundational technical leader in the perception organization, the incoming engineer will define how machines transform raw sensor data from cameras, LiDAR, radar, and audio into rich representations of the physical environment. Working across AI research, robotics, and autonomy, the individual will shape perception architectures that connect traditional capabilities with emerging foundation models while remaining deeply hands-on.
Ideal candidates are seasoned machine learning practitioners who thrive in ambiguous problem spaces and possess a strong track record of technical leadership. The position suits an engineer who enjoys balancing model quality with strict latency, compute, and reliability constraints in real-world operating environments. Anyone joining the team will collaborate closely with peers to establish the technical bar for perception while driving architectures that bridge software and physical hardware.
What you will do
- Define and help build the technical architecture for next-generation perception systems.
- Develop machine learning systems that transform multimodal sensor inputs into useful representations of the physical environment.
- Design and develop deep learning architectures for detection, segmentation, tracking, classification, scene understanding, and 3D perception.
- Explore how modern foundation models and world models can complement or replace components of traditional perception pipelines.
- Make architectural decisions spanning data, model design, training, evaluation, inference, and deployment.
- Establish evaluation methodologies and metrics that accurately measure perception performance in real-world operating environments.
- Provide technical leadership across the organization through architecture reviews, mentorship, technical direction, and hands-on engineering.
What you need
- Deep expertise in machine learning and computer vision, with substantial experience building sophisticated perception systems.
- Strong understanding of modern deep learning architectures and their application to visual and multimodal perception.
- Experience working with one or more real-world sensor modalities such as cameras, LiDAR, radar, audio, or depth sensors.
- Familiarity with sensor fusion, multimodal learning, 3D perception, scene understanding, or related areas.
- Demonstrated understanding of the full ML lifecycle, including data strategy, training, architecture, evaluation, optimization, and deployment.
- Experience designing machine learning systems that operate under real-world latency, compute, reliability, and safety constraints.
- Strong software engineering fundamentals with the ability to remain deeply hands-on in Python and/or C++.
Benefits
- Medical, Dental, Vision, Disability, and Life Insurance
- Flexible Spending Account / Health Savings Account Options
- 401(k) and Equity
- Sick Time, Unlimited Flexible Time Off, and Paid Holidays
- Paid Parental Leave and Pre-Tax Commuter Benefit Plan
- Team lunch in the SoMa office every Tuesday and Thursday
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
This role is based in the San Francisco office. All office-based teams work onsite, five days a week.
What is the salary range for this position?
The base salary range for this role is $275,000 - $321,000 per year. Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.
What sensor modalities will I be working with?
You will work across camera, LiDAR, radar, audio, and other sensor modalities. The goal is to build perception systems capable of operating in complex, dynamic real-world environments.
What kind of team will I be collaborating with?
You will partner closely with researchers and engineers working across world models, action models, robotics, autonomy, and ML infrastructure. The team consists of roboticists, engineers, operators, and builders.
The application is on the official ATOMS Careers page careers page.
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