Staff Systems Engineer - Camera
1X Technologies
Listing collected from 1X Technologies's career site. NextChapter is independent of 1X Technologies.
San Carlos, CA · $250k–$300k a year · Posted October 22, 2026
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Where San Carlos, CA ranks
Where San Carlos, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for manufacturing and industrial pay after cost of living$176k · of 35
- #4Best cities for mid-career professionals in the West Coast65% · of 71
- #7Cities that post pay most often45% · of 100
- #8Best cities for mid-career professionals65% · of 100
- #9Best all-round cities for mid-career professionals in the West Coast63 / 100 · of 39
- #10Best cities for pay after cost of living in California$176k · of 32
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing pays about $275,000 a year. Across 33 open staff systems engineer listings that state pay, the middle half runs $177,000 to $222,500 and the median is $222,000. That is 24% above the median, above the middle half of those listings.
Listed pay is what employers advertise, not what people are paid.
Staff Systems Engineer salaries by state · Check your own pay
How AI is used in this kind of work
Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
About 1X
We're building humanoid robots that work in home - doing the chores, handling the tasks, and giving people their time back. Simple, but it's not.
To do this right, we have to solve robotics, AI, manufacturing - at the same time, at scale, in a form factor that has to be safe enough to live with your family. If you're inspired by this, you'll thrive here. We've been at this since 2014 and we're at the point where the hard problems are behind us and the hard work is in front of us.
NEO is our flagship - a home robot designed to move, learn, and operate in the real world alongside real people. We're not demoing it - we're shipping it. We're excited to meet you, if this excites you.
If you've spent your career working on problems that matter and want to see them actually reach the world - this is that moment. We're scaling, we're hiring with intention, and we need people who want to build something that will genuinely change how humans spend their time - safely creating abundance for all.
About the Team
The Core team builds and owns the core C++ infrastructure that NEO’s entire stack runs on, from sensor pipelines, motor control interfaces, networking, inter-process communication, and the foundational libraries that ship on every robot. Our code executes thousands of times per second on hardware moving through the real world, and its correctness and performance directly determines what every other team can build and ship. If you want to work on the systems layer that makes physical AI possible at scale, this is that team.
Your Charter
Own the camera stack NEO sees through, from the sensor and lens selected for the robot to the calibrated, rectified frames every perception model consumes. This is critical-path work: no vision model is better than the images it is handed, and nothing downstream survives a camera that is miscalibrated, badly tuned, or quietly dropping frames. You will own that path from vendor selection through end-of-line calibration on the production line and out to robots already working in homes.
Key Outcomes
- Own camera selection end to end: define sensor, lens, and module requirements with the hardware and perception teams, run the trade studies, and carry a choice through vendor engagement and bring-up on real hardware
- Deliver a camera pipeline that holds up in production: sensor drivers, multi-camera synchronization and timestamping, and frame delivery that meets its latency budget without dropping frames or destabilizing timestamps
- Tune the image path for machines rather than for people: exposure, white balance, and dynamic range chosen so perception models are accurate in real homes, including the low light and hard backlight a living room actually presents
- Make calibration a production process, not a lab procedure: intrinsics and extrinsics calibrated on the line inside cycle time, validated automatically, monitored for drift across the fleet, and recoverable in the field
Key Competencies
- Camera systems depth understanding sensors, optics, and ISP as one system, and how an image travels a robotics stack from capture through transport, compression, and transformation to the model that consumes it
- Lives at the hardware boundary debugging across MIPI CSI-2, serdes links, I2C, PoE, and power and clock sequencing, and treating dropped frames, timestamp instability, and bandwidth limits as everyday failure modes rather than mysteries
- Calibration rigor treating calibration as measurement with error bars, reasoning about tolerances and uncertainty, and knowing how a calibration error propagates into what a perception model gets wrong
- Thinks in fleets, not units designing calibration and diagnostics that survive a production line at volume and robots already in homes, not just a bench with a careful operator
Minimum Requirements
- 5+ years shipping camera or imaging software in production systems: robotics, autonomous vehicles, consumer devices, or AR and VR
- Hands-on experience bringing up image sensors on embedded Linux, including V4L2, MIPI CSI-2, and the driver and device tree work that comes with it
- Demonstrated experience with camera intrinsic and extrinsic calibration, including validating calibration quality rather than trusting a solver's output
- Strong C++ in performance-critical systems, with the profiling and debugging habits to find where frames and milliseconds actually go
Preferred Skills
- Experience with ISP tuning and image quality evaluation, especially where the consumer is a perception model rather than a person
- Experience taking calibration into manufacturing: fixture and station design, cycle time, yield, and failure analysis on build data
- Familiarity with CUDA or GPU image processing and zero-copy image transport between processes
- Background in multi-camera synchronization, stereo rectification, or camera-IMU time alignment
What does a successful 1X Team Member look like
Team members at 1X who thrive here are builders. They move fast, own their work completely, and treat time like it's the one thing you can't get back - because it is. They say what they mean, finish what they start, and hold themselves to a standard before anyone has to ask. We push each other to be better, and we do it with honesty and respect.
Compensation
$250,000 - $300,000 + Equity
Benefits
- Comprehensive medical, dental, and vision coverage
- Generous paid time off, company holidays, and parental leave
- 401(k) plan with company match (100% on the first 3% of contributions, 50% on the next 2%)
- Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA) options
- Commuter benefits (transit and parking)
- Short-term and long-term disability, and life insurance
- Employee Assistance Program (EAP) for mental health, financial, and personal support
- Onsite snacks and catered lunches
Equal Opportunity Employer
1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, justice system impact, or any other characteristic protected under applicable federal, state, or local law.