Machine Learning Engineer Jobs at Zoox with Visa Sponsorship
Machine Learning Engineer jobs at Zoox involve working on perception, prediction, and planning systems that power a robotaxi designed for dense urban environments, as the company builds autonomous vehicles from the ground up. Zoox has an established track record of sponsoring work visas across multiple categories for this function.
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Get Access To All JobsINTRODUCTION
The Perception team at Zoox is responsible for the robot’s understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks. You will architect and optimize high-performance deep learning models that generate dense, temporally consistent voxel representations of the driving environment. This work is critical for enabling our vehicle to navigate complex urban scenarios, handle rare obstacles, and drive safely in tight spaces by providing precise geometry and motion estimates to downstream planners.
ROLE AND RESPONSIBILITIES
In this role, you will...
- Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow.
- Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities.
- Engineer temporal processing modules to improve the stability and consistency of predictions over time.
- Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints.
- Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering.
QUALIFICATIONS
- MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.
- Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures.
- Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration.
- Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences.
- Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation.
BONUS QUALIFICATIONS
- Experience optimizing models for TensorRT/CUDA to achieve low-latency inference.
- Familiarity with sparse convolutions or query-based architectures for efficient 3D processing.
- Experience with Vision Language Model, or multi-modal 3D foundation model, or World Model, or VLA.
COMPENSATION
- Base Salary Range: There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
ABOUT ZOOX
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
ACCOMMODATIONS
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
INTRODUCTION
The Perception team at Zoox is responsible for the robot’s understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks. You will architect and optimize high-performance deep learning models that generate dense, temporally consistent voxel representations of the driving environment. This work is critical for enabling our vehicle to navigate complex urban scenarios, handle rare obstacles, and drive safely in tight spaces by providing precise geometry and motion estimates to downstream planners.
ROLE AND RESPONSIBILITIES
In this role, you will...
- Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow.
- Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities.
- Engineer temporal processing modules to improve the stability and consistency of predictions over time.
- Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints.
- Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering.
QUALIFICATIONS
- MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.
- Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures.
- Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration.
- Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences.
- Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation.
BONUS QUALIFICATIONS
- Experience optimizing models for TensorRT/CUDA to achieve low-latency inference.
- Familiarity with sparse convolutions or query-based architectures for efficient 3D processing.
- Experience with Vision Language Model, or multi-modal 3D foundation model, or World Model, or VLA.
COMPENSATION
- Base Salary Range: There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
ABOUT ZOOX
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
ACCOMMODATIONS
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
See all Machine Learning Engineer Jobs at Zoox
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Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Zoox
Align your ML focus to AV-specific domains
Zoox hires ML Engineers for perception, motion forecasting, and sensor fusion, not general-purpose ML. Frame your resume around LiDAR, camera, or radar data pipelines so your profile matches their active hiring areas rather than broad machine learning.
Prepare your specialty occupation documentation early
H-1B petitions for ML roles require demonstrating the position meets specialty occupation standards. Pull together degree transcripts, a detailed job description from Zoox, and any publications or patents that establish your theoretical depth in relevant subfields before your offer stage.
Use Migrate Mate to filter Zoox ML openings by visa type
Zoox posts across multiple ML Engineering tracks simultaneously. Migrate Mate lets you filter Zoox roles by the visa categories they sponsor, so you can target the openings explicitly matched to your current status, whether OPT, H-1B, or E-3.
Confirm your OPT STEM extension eligibility before accepting
Zoox is E-Verify enrolled, which is required for the 24-month STEM OPT extension. Before signing an offer, verify your degree is on the current STEM Designated Degree Program list so your extension timeline lines up with their onboarding plans.
Ask recruiters about cap-exempt petition timing
If you missed the H-1B lottery, ask Zoox's recruiting team whether they'll file a cap-exempt petition if you hold concurrent status at a qualifying institution or previous cap-counted approval. Autonomous vehicle research roles can sometimes support this pathway.
Account for PERM timing if you're targeting a Green Card
EB-2 and EB-3 PERM labor certification processing at DOL currently runs many months before an I-140 can be filed. Raise permanent residency intentions with Zoox's immigration team early so they can schedule the recruitment process without delaying your timeline.
Frequently Asked Questions
Does Zoox sponsor H-1B visas for Machine Learning Engineers?
Yes, Zoox sponsors H-1B visas for Machine Learning Engineer roles. The company has a consistent pattern of petitioning for engineers across its autonomy stack, including perception, prediction, and planning functions. Because ML Engineering clearly meets USCIS specialty occupation standards, H-1B petitions for these roles are well-supported by degree requirements in computer science, electrical engineering, or a closely related field.
Which visa types does Zoox commonly use for Machine Learning Engineer roles?
Zoox sponsors H-1B, H-1B1 visa, E-3 visa, TN visa, J-1 visa, and F-1 OPT and CPT for Machine Learning Engineers, and supports EB-2 and EB-3 Green Card pathways for longer-term employees. Australian citizens can use the E-3 visa as an H-1B alternative with no lottery. Canadian and Mexican nationals working in qualifying engineering occupations may be eligible for TN visa status.
How do I apply for Machine Learning Engineer jobs at Zoox?
Search for Machine Learning Engineer openings directly on Zoox's careers page, or browse their current postings filtered by visa sponsorship eligibility on Migrate Mate. Zoox typically screens for strong fundamentals in deep learning, experience with large-scale data systems, and familiarity with at least one autonomous vehicle domain such as perception or sensor fusion. A coding screen and systems design interview are standard parts of the process.
What qualifications does Zoox expect for Machine Learning Engineer candidates?
Zoox generally looks for a master's or PhD in computer science, machine learning, robotics, or a closely related field, along with hands-on experience building and deploying models at scale. For senior roles, domain depth in areas like 3D object detection, trajectory prediction, or onboard inference optimization carries significant weight. Strong programming skills in Python and C++ are expected across most ML Engineering tracks.
How do I manage timing between my visa status and a Zoox offer?
If you're on F-1 OPT, confirm your remaining authorized period before your anticipated start date, since Zoox's onboarding and background check process can take several weeks. For H-1B transfers, Zoox can file a concurrent petition so you're covered on day one. If you're between roles and in a 60-day grace period, prioritize getting the offer signed and the petition filed before that window closes.