Senior Perception Engineer
San Francisco, CAFull-time$208–245K/yrPosted 4w agoStill listed 6 days ago
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At a glance
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Job overview
Pronto AI develops production-deployed autonomous haulage systems for mines, quarries, and construction sites. The Perception Engineer builds systems that interpret sensor data for autonomous machines, working across computer vision, machine learning, robotics, and autonomous systems. The role is based in the San Francisco office and works onsite five days a week. Publications or significant research contributions are a plus, but are not required.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Who we are
Pronto AI is a global leader in commercializing autonomous vehicle (AV) technology, deploying Autonomous Haulage Systems (AHS) that automate operations in mines, quarries, and construction sites worldwide. While much of the industry remains in R&D, we deliver real, production-ready autonomy that is already operating in the field.
We are on a mission to make mining operations safer, smarter, and more efficient through cutting-edge technology, and we are building toward becoming the world’s first profitable AV technology company.
What you'll do
We are seeking a Perception Engineer to develop the systems that enable our 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.
Depending on your background and area of expertise, you may:
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Design, train, and deploy machine learning models for perception in autonomous systems.
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Develop algorithms for object detection, classification, segmentation, tracking, and scene understanding.
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Build systems for 3D perception and geometric reasoning using cameras, LiDAR, radar, or other sensors.
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Develop approaches for multi-sensor and multi-modal fusion, combining complementary sensor information into robust representations of the environment.
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Build temporal models that reason about objects, motion, trajectories, and changes in the environment over time.
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Improve perception performance across challenging real-world conditions, including occlusion, sensor noise, changing environments, and edge cases.
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Develop data, training, evaluation, and experimentation pipelines that accelerate perception development.
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Define metrics and evaluation methodologies that connect offline model performance to real-world system behavior.
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Optimize perception models and systems for deployment on resource-constrained or latency-sensitive robotic platforms.
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Investigate failures observed in deployed systems and translate those findings into improvements across models, data, and architecture.
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Collaborate closely with AI Research, Robotics, ML Infrastructure, Software, Hardware, and Systems Engineering teams.
What we're looking for
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3-5 years of relevant experience working with perception systems and computer vision & machine learning models.
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Strong software engineering skills in Python and/or C++.
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Experience developing perception systems for autonomous vehicles, robotics, drones, industrial automation, or other embodied systems.
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Experience with camera, LiDAR, radar, IMU, or other robotic sensor modalities.
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Experience with multi-modal or multi-sensor architectures.
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Knowledge of 3D geometry, coordinate transformations, calibration, localization, or state estimation.
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Experience deploying ML models into real-time or safety-critical systems.
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Experience optimizing models for latency, compute, memory, or power constraints.
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Experience working with large-scale perception datasets and training infrastructure.
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Experience diagnosing long-tail failures and improving production perception systems through data-driven iteration.
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Experience taking research ideas from experimentation through deployment on physical systems.
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Publications or significant research contributions in computer vision, machine learning, robotics, or related fields are a plus, but not required.
Why join us
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Work on real, production-deployed autonomy.
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Build technology that directly improves safety, efficiency, and productivity.
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Tackle complex challenges in demanding, real-world environments.
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Be part of a fast-moving team with high ownership and impact.
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See your work deployed and making a difference in the field.
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Collaborate closely with experienced engineers and industry operators.
What else you need to know
This role is based in our San Francisco office location. As a company driven by innovation and continuous change, close collaboration is essential. We’re constantly reimagining our industry, creating new products, and refining our processes, and 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 $208,000 - $245,000 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):
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Medical, Dental, Vision, Disability, and Life Insurance
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Flexible Spending Account / Health Savings Account Options
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401(k)
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Equity
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Sick Time, Unlimited Flexible Time Off, and Paid Holidays
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Paid Parental Leave
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Pre-Tax Commuter Benefit Plan
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Team lunch in our SoMa office every Tuesday and Thursday
Benefits are subject to change at the company's discretion. Pronto accepts applications on an ongoing basis.
Ready to join us as we serve those who serve others?
#LI-Onsite
How this job compares
Set against the 5,922 open Machine Learning Engineer jobs on Olive Jobs, counted October 28, 2026.
- Pay
- This posting$208–245K/yr
- California median$174–260K/yr1,329 salary ranges
- US median$145–245K/yr4,675 salary ranges
This range's midpoint, $227K, is 4% above the California median midpoint ($218K) — in the middle half of Machine Learning Engineer salary ranges in California.
- Openings
- Olive Jobs lists 1,805 open Machine Learning Engineer jobs in California and 5,922 across the US. 5% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,753 postings).
- Education
- 2,404 of the 5,922 open Machine Learning Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 28, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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