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About the Role
We are seeking a Perception Engineer to develop systems that enable autonomous machines to understand and interact with the physical world. You will work on perception problems at the intersection of computer vision, machine learning, robotics, and autonomous systems, building models and systems that transform real-world sensor data into reliable representations of the environment.
Responsibilities
- Design, train, and deploy machine learning models for perception in autonomous systems.
- Develop algorithms for object detection, classification, segmentation, tracking, and scene understanding.
- Build systems for 3D perception and geometric reasoning using cameras, LiDAR, radar, or other sensors.
- Develop approaches for multi-sensor and multi-modal fusion, combining complementary sensor information into robust representations of the environment.
- Build temporal models that reason about objects, motion, trajectories, and changes in the environment over time.
- Improve perception performance across challenging real-world conditions, including occlusion, sensor noise, changing environments, and edge cases.
- Develop data, training, evaluation, and experimentation pipelines that accelerate perception development.
- Define metrics and evaluation methodologies that connect offline model performance to real-world system behavior.
- Optimize perception models and systems for deployment on resource-constrained or latency-sensitive robotic platforms.
- Investigate failures observed in deployed systems and translate those findings into improvements across models, data, and architecture.
- Collaborate closely with AI Research, Robotics, ML Infrastructure, Software, Hardware, and Systems Engineering teams.
Requirements
- 3-5 years of relevant experience working with perception systems and computer vision & machine learning models.
- Strong software engineering skills in Python and/or C++.
- Experience developing perception systems for autonomous vehicles, robotics, drones, industrial automation, or other embodied systems.
- Experience with camera, LiDAR, radar, IMU, or other robotic sensor modalities.
- Experience with multi-modal or multi-sensor architectures.
- Knowledge of 3D geometry, coordinate transformations, calibration, localization, or state estimation.
- Experience deploying ML models into real-time or safety-critical systems.
- Experience optimizing models for latency, compute, memory, or power constraints.
- Experience working with large-scale perception datasets and training infrastructure.
- Experience diagnosing long-tail failures and improving production perception systems through data-driven iteration.
- Experience taking research ideas from experimentation through deployment on physical systems.
Skills
- Computer Vision
- Machine Learning
- Robotics
- Autonomous Systems
- Python
- C++
- 3D Geometry
- Coordinate Transformations
- Calibration
- Localization
- State Estimation
Location
- San Francisco
Work Type
- Onsite
Experience Level
- 3-5 years
Salary/Compensations
- $208,000 - $245,000 per year
Benefits
- Medical, Dental, Vision, Disability, and Life Insurance
- Flexible Spending Account / Health Savings Account Options
- 401(k)
- Equity
- Sick Time, Unlimited Flexible Time Off, and Paid Holidays
- Paid Parental Leave
- Pre-Tax Commuter Benefit Plan
- Team lunch in our SoMa office every Tuesday and Thursday
About the Company
- Atoms is building the machines that power the next era of progress.
- Over the last decade, software has transformed the digital world. But the physical world, where food is made, minerals are mined, goods are moved, and industries are run, remains far less intelligent, far less efficient, and far more constrained. We’re changing that.
- Atoms builds Physical AI— real-world robots for the industries that move civilization forward, starting with food, mining, and transport.
- Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, more scalable, and more productive.
- This work requires more than robotics. It requires deep integration across hardware, software, AI, operations, manufacturing, and real estate.
- We don’t just build machines in a lab. We deploy them into real environments, operate them, learn from them, and improve them until they work at scale.
- We are roboticists, engineers, operators, and builders.
- We believe the next great technology companies will not only transform information, but the physical systems that shape everyday life.
- If you want to work on hard problems with real-world impact, join us.