Pay
Higher than most similar jobs
$200K–$280K against $166K–$240K, the middle half of what similar US postings state.
From 1,383 postings in the last year. Stated ranges, not salaries paid.
Senior/Staff Machine Learning Engineer, Perception
South San Francisco, CA
Open 3 months, first seen by us 109 days ago- Pay
USD 200,000–280,000/year · Base — pay source
Passion for how we feed, build, move, and maintain the world. The US base salary range for this full-time position is $200,000 to $280,000 + equity + benefits + unlimited PTO The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job-related skills, experience, and relevant education or specialty training. Your recruiter can share more about the specific salary range during the hiring process.
Salary 200,000 – 280,000 USD per year Benefits
Read the full posting- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: Full Time
From the employer’s posting
What you’ll work on
Full postingWe're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments.
The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception.
Develop real-time perception models for open-world obstacle and terrain understanding
Build camera and LiDAR fusion into a unified 3D/BEV representation
Optimize models for low-latency inference on resource-constrained hardware
Design auto-labeling pipelines using foundation models and teacher-student distillation
Build data and evaluation pipelines that surface failures fast
From the employer’s posting
We're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments. You'll develop computer vision and machine learning systems that turns noisy camera and LiDAR data into robust 3D scene understanding — enabling heavy equipment to operate safely through dust, glare, occlusion, and whatever messy conditions a working site throws at it.
The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception. You'll be at the center of that shift. This role is hands-on: you'll write production-grade software, distill and optimize models for embedded hardware, and validate your work on real machines at operating around the world.
Develop real-time perception models for open-world obstacle and terrain understanding.
Build multi-modal fusion that combines camera and LiDAR into a unified 3D/BEV representation
Optimize models for low-latency inference on resource-constrained hardware
Design auto-labeling pipelines that leverage foundation models and teacher-student distillation
Design data and evaluation pipelines that curate large multi-sensor datasets and surface failures fast
Education & alternatives
What You'll Bring - A MS/PhD in Computer Science, AI, or a related field, or 6+ years of industry experience building vision-based perception systems. - Deep expertise developing and deploying modern perception models: detection, segmentation, mono/stereo/metric depth, BEV/occupancy, sensor fusion, and 3D scene understanding.
Benefits in the posting
Full benefits wording- 100% covered medical, dental, and vision for the employee (partner, children, or family is additional)
- Commuter Benefits
- Flexible Spending Account (FSA or HSA)
- Life Insurance
- Short- and Long-Term Disability
- 401k Plan
- Stock Options
- Employment type
- Full Time
From the employer’s posting.
About Agtonomy
At Agtonomy, we’re not just building tech—we’re transforming how vital industries get work done.
In the employer’s words · Read in context
Posting record
Report an errorOpen 3 monthsWe first saw this posting 109 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 25, 2026109 days ago
- Recorded sightings
- 41
- Last seen by us
- Nov 11, 2026
- Employer says posted
- Jul 9, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 109
Up longer than most. Similar jobs usually come down between day 8 and day 75.
From 5,207 similar postings that came down. Coming down is not always a hire.
Agtonomy is hiring
2 open jobs
- No new data jobs since July
See how this role fits your experience
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- Python
- PyTorch
- TensorFlow
Where the posting names them
- Experience handling large datasets efficiently and organizing them for labeling, training and evaluation. - Fluency in Python with PyTorch/TensorFlow/OpenCV and the ability to write efficient, production-ready code for real-time systems. - Proven ability to design experiments, analyze metrics (mAP, IoU, latency/throughput, and calibration/ECE), and optimize to meet stringent real-world performance and safety requirements.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Us
At Agtonomy, we’re not just building tech—we’re transforming how vital industries get work done. Our Physical AI and fleet services turn heavy machinery into intelligent, autonomous systems that tackle the toughest challenges in agriculture, turf, and beyond. Partnering with industry-leading equipment manufacturers, we’re creating a future where labor shortages, environmental strain, and inefficiencies are relics of the past. Our team is a tight-knit group of bold thinkers—engineers, innovators, and industry experts—who thrive on turning audacious ideas into reality. If you want to shape the future of industries that matter, this is your shot.
About the Role
We're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments. You'll develop computer vision and machine learning systems that turns noisy camera and LiDAR data into robust 3D scene understanding — enabling heavy equipment to operate safely through dust, glare, occlusion, and whatever messy conditions a working site throws at it.
The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception. You'll be at the center of that shift. This role is hands-on: you'll write production-grade software, distill and optimize models for embedded hardware, and validate your work on real machines at operating around the world.
What You'll Do
- Develop real-time perception models for open-world obstacle and terrain understanding.
- Build multi-modal fusion that combines camera and LiDAR into a unified 3D/BEV representation, robust to occlusions, sensor degradation, and GNSS outages.
- Optimize models for low-latency inference on resource-constrained hardware, balancing accuracy and performance.
- Design auto-labeling pipelines that leverage foundation models and teacher-student distillation to scale labeling and close the loop from real-world field interventions.
- Design data and evaluation pipelines that curate large multi-sensor datasets and surface failures fast, with strong visualization and debugging tooling.
- Analyze performance metrics and iterate on algorithms to improve accuracy and efficiency of various perception subsystems.
What You'll Bring
- A MS/PhD in Computer Science, AI, or a related field, or 6+ years of industry experience building vision-based perception systems.
- Deep expertise developing and deploying modern perception models: detection, segmentation, mono/stereo/metric depth, BEV/occupancy, sensor fusion, and 3D scene understanding.
- Fluency adapting, fine-tuning, and distilling large pre-trained vision and vision-language models.
- Strong grounding in multi-sensor integration (camera, LiDAR, radar): calibration, spatiotemporal sync, and cross-modal fusion.
- Experience handling large datasets efficiently and organizing them for labeling, training and evaluation.
- Fluency in Python with PyTorch/TensorFlow/OpenCV and the ability to write efficient, production-ready code for real-time systems.
- Proven ability to design experiments, analyze metrics (mAP, IoU, latency/throughput, and calibration/ECE), and optimize to meet stringent real-world performance and safety requirements.
- An eagerness to get your hands dirty and agility in a fast-moving, collaborative, small team environment with lots of ownership.
What Makes You a Strong Fit
- Experience architecting multi-sensor ML systems from scratch.
- Experience building auto-labeling / data-engine flywheels at scale.
- Experience with compute-constrained pipelines including optimizing models to balance the accuracy vs. performance tradeoff, leveraging TensorRT, model quantization, etc.
- Familiarity with emerging predictive world models for anticipation, anomaly detection, or closed-loop simulation, and adjacent policy paradigms such as Vision-Language-Action (VLA) and World-Action (WAM) models.
- Experience with compute-constrained deployment: TensorRT, model quantization, and custom CUDA operations.
- Publications at top-tier perception/robotics venues (CVPR, ICRA, CoRL, RSS, etc.).
- Passion for how we feed, build, move, and maintain the world.
The US base salary range for this full-time position is $200,000 to $280,000 + equity + benefits + unlimited PTO
The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job-related skills, experience, and relevant education or specialty training. Your recruiter can share more about the specific salary range during the hiring process.
Salary
200,000 – 280,000 USD per year
Benefits
• 100% covered medical, dental, and vision for the employee (partner, children, or family is additional)
• Commuter Benefits
• Flexible Spending Account (FSA or HSA)
• Life Insurance
• Short- and Long-Term Disability
• 401k Plan
• Stock Options
• Collaborative work environment working alongside passionate mission-driven team!
Employment type
Full Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Passion for how we feed, build, move, and maintain the world. The US base salary range for this full-time position is $200,000 to $280,000 + equity + benefits + unlimited PTO The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job-related skills, experience, and relevant education or specialty training. Your recruiter can share more about the specific salary range during the hiring process.
More source context
Salary 200,000 – 280,000 USD per year Benefits
- Location & working pattern
South San Francisco, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.