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 Offline Driving Intelligence (ODIN) team at Zoox is leveraging the latest in AI to craft algorithms that understand the world. We leverage large models first offline and we devise a path of impact into our self-driving robot, enabling safe and efficient navigation in complex environments.
As an engineer in the ODIN team, you will develop advanced multimodal large language models that enhance environmental understanding. You'll develop and fine-tune these models for off-vehicle analysis while working with the onboard team to deliver impact in our robotaxi platform, ensuring they can efficiently identify hazards and interpret driving restrictions with minimal latency. Working alongside world-class engineers and researchers, you'll leverage premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions, directly impacting productivity, safety and the capability of Zoox's autonomous system.
ROLE AND RESPONSIBILITIES
- Lead the development of multimodal large language models that enhance our robotaxis' understanding of complex urban environments
- Design effective model architectures and sophisticated training techniques, leveraging all the inputs from our sensor stack and the overall large scale data we have at Zoox
- Drive end-to-end ML solutions from research to production, utilizing Zoox's extensive data pipelines and infrastructure to improve autonomous driving capabilities
- Collaborate with perception, planning, safety, and systems teams to integrate your models into the vehicle's decision-making pipeline
- Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of Zoox's autonomous system
BASIC QUALIFICATIONS
- MS or PhD in Computer Science, Machine Learning, or related technical field
- Demonstrated experience training and deploying large language models (LLMs)
- Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation
- Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
- Experience training with large scale datasets (e.g. tens of millions of videos)
PREFERRED QUALIFICATIONS
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with autonomous robotics systems
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. 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 Offline Driving Intelligence (ODIN) team at Zoox is leveraging the latest in AI to craft algorithms that understand the world. We leverage large models first offline and we devise a path of impact into our self-driving robot, enabling safe and efficient navigation in complex environments.
As an engineer in the ODIN team, you will develop advanced multimodal large language models that enhance environmental understanding. You'll develop and fine-tune these models for off-vehicle analysis while working with the onboard team to deliver impact in our robotaxi platform, ensuring they can efficiently identify hazards and interpret driving restrictions with minimal latency. Working alongside world-class engineers and researchers, you'll leverage premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions, directly impacting productivity, safety and the capability of Zoox's autonomous system.
ROLE AND RESPONSIBILITIES
- Lead the development of multimodal large language models that enhance our robotaxis' understanding of complex urban environments
- Design effective model architectures and sophisticated training techniques, leveraging all the inputs from our sensor stack and the overall large scale data we have at Zoox
- Drive end-to-end ML solutions from research to production, utilizing Zoox's extensive data pipelines and infrastructure to improve autonomous driving capabilities
- Collaborate with perception, planning, safety, and systems teams to integrate your models into the vehicle's decision-making pipeline
- Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of Zoox's autonomous system
BASIC QUALIFICATIONS
- MS or PhD in Computer Science, Machine Learning, or related technical field
- Demonstrated experience training and deploying large language models (LLMs)
- Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation
- Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
- Experience training with large scale datasets (e.g. tens of millions of videos)
PREFERRED QUALIFICATIONS
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with autonomous robotics systems
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. 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 64+ 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.