Who we are
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. About the role We are seeking a Senior Systems Engineer to own diagnostics and failure analysis across our development fleet. In this role, you will take a failure from a log to an assigned root cause, owning the triage classification, the severity model, and the diagnostic tooling that determines how quickly we know what failed. You will build the diagnostic coverage and automated classification that turns failure analysis from an engineering activity into a process that runs such that only new failures reach a person. The role spans multiple vehicle platforms with different hardware, compute, and software, and requires regular time in the garage and around vehicles.
What you’ll do
Triage. Classify failures as software, firmware, hardware, data path, or system-level regressions, and route them with evidence.
Root cause analysis. Investigate novel failures using logs, telemetry, bus traces, and video, and establish the root cause.
Diagnostic tooling. Build the parsing, correlation, and visualization that make large log datasets tractable for engineers outside this role.
Automated classification. Build the frameworks that detect known failure signatures automatically, so recurrence is caught by software.
Data path integrity. Own monitoring for the logging path itself: dropped frames, timestamp drift, bandwidth and storage limits, and the alerting that catches a vehicle producing unusable data the same day.
Severity and trend analysis. Categorize severity consistently and identify the failure clusters that should set engineering priority.
Documentation. Set the standard for what a complete root cause analysis looks like here, and author the troubleshooting guides.
What we’re looking for
Bachelor's or master's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field required.
6+ years in systems integration, diagnostics, or hardware and software interface engineering on vehicles.
L4 program or production ADAS experience.
A track record of diagnosing failures that spanned hardware and software, with specific examples where you established the root cause.
Ability to correlate hardware symptoms and video evidence with telemetry and bus data into a concrete timeline.
Sensor-level troubleshooting depth on cameras, lidar, radar, GNSS and IMU, including timing failure modes.
Strong working knowledge of vehicle networks and diagnostics, including CAN, CAN FD, Automotive Ethernet, and DTCs, and how failures present at each layer.
Python and command line log analysis at the level of building production tools
Automated triage or anomaly detection built over fleet data.
Experience with monitoring and observability platforms and with log management at fleet scale.
Working experience with cloud storage and databases for telemetry: object storage, SQL, and time series or NoSQL stores.
Experience with a data collection or logging fleet, particularly diagnosing data path problems at volume.
Ability to work onsite five days a week in San Francisco, with periodic travel to test sites.
Why join us
At Atoms, you’ll work on one of the defining challenges of our time—bringing automation into the physical world to drive real, lasting impact. We exist to uncover valuable unknown truths and turn them into progress, which means constantly pushing beyond what’s known and building what doesn’t yet exist. The work is ambitious and often challenging, but it’s grounded in a shared sense of purpose and a team committed to seeing it through together. Our work only matters if it serves others, and we know that meaningful progress depends on the trust of the people we serve and the strength of our team—so we invest in both, creating an environment where you can do your best work and grow.
What else you need to know
This role is based in our San Francisco office. Atoms is a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That’s why all of our office-based teams work onsite, five days a week.
The base salary range for this role is $176,000 - $242,000 per year.
Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.
Base salary is just one part of your total rewards package. You may also be eligible for equity awards.
Benefits Summary (USA Full-Time Exempt Employees):
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
Benefits are subject to change at the company's discretion. Atoms accepts applications on an ongoing basis.
Ready to join us as we serve those who serve others?
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