Ouster
Sr. Machine Learning Engineer (Perception and Tracking)
San Francisco, California, USA · Senior · full-time
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$13,149 more — $193,149 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $193,149 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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from this employer's Department of Labor filings
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Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- We've transformed LIDAR from an analog device with thousands of components to an elegant digital device powered by one chip-scale laser array and one CMOS sensor.
- Our advanced sensor hardware and vision algorithms are used in autonomous cars, robotics, industrial, and smart infrastructure applications (among many others).
- If you're motivated by solving big problems, we're hiring key roles across the company and need your help!
Responsibilities
- Architect Unified Models: Design and train DNN models that perform Object Detection and Tracking simultaneously, leveraging temporal information to improve consistency.
- Optimize models for real-time inference and on-device deployment.
- Data Strategy: Develop training recipes for data-constrained environments and effective post-training strategies.
- Design and train DNN models that perform Object Detection and Tracking simultaneously, leveraging temporal information to improve consistency.
- Develop training recipes for data-constrained environments and effective post-training strategies.
Requirements
- Core Stack: 5+ years proficiency in Python and PyTorch.
- 3+ years proficiency in C++ for production deployment and optimization.
- Architecture Internals: Proven experience not being dependent on "out-of-the-box" APIs.
- You have a track record of modifying model architectures via extensive experimentation to meet specific requirements.
- This role requires a deep knowledge of neural network architectures.
- 5+ years proficiency in Python and PyTorch.
- Proven experience not being dependent on "out-of-the-box" APIs.
Nice to have
- 3D / LiDAR Experience: Hands-on experience with 3D Point Cloud data (LiDAR) is a massive plus.
- Deployment Tools: Experience with TensorRT, ONNX Runtime, or edge-specific hardware (NVIDIA Jetson, etc.).
- You do not need to meet all of these requirements to be the ideal candidate for this role.
- Ouster is an Equal Employment Opportunity employer that pursues and hires a diverse workforce.
- Ouster also strives for a healthy and safe workplace, and prohibits harassment of any kind.
- Pursuant to the San Francisco Fair Chance Ordinance, Ouster considers qualified applicants with arrest and conviction records for employment.
- Hands-on experience with 3D Point Cloud data (LiDAR) is a massive plus.
- Deployment Tools:
Compensation
- $180k-$220k
This listing is sourced directly from Ouster's careers page and normalized into a canonical job model.