ML Software Engineer Jobs at Zoox with Visa Sponsorship
ML Software Engineer jobs at Zoox involve working on perception, prediction, and planning systems for fully autonomous vehicles built from the ground up, where safety-critical performance standards are essential. Zoox sponsors a broad range of work visas for this function, making it a realistic target for international candidates in the autonomous vehicle space.
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Get Access To All JobsINTRODUCTION
Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.
The Opportunity
Are you excited to lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here.
In This Role, You Will
- Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience.
- Lead the design, implementation, and operation of cutting-edge ML Training and inference performance optimization techniques.
- Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
- Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.
BASIC QUALIFICATIONS
- Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
- Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
- Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.
- Proficient in Python and C++
- Experience with model compression techniques to reduce model size and improve performance.
PREFERRED QUALIFICATIONS
- 10+ years of total experience, including 4+ years of working on large-scale model training or inference platforms.
- Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
COMPENSATION
- Base Salary Range: $242,000 - $389,000 a year
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. Follow us on LinkedIn.
ACCOMMODATIONS
If you need an accommodation to participate in the application or interview process please reach out to [email protected] 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
Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.
The Opportunity
Are you excited to lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here.
In This Role, You Will
- Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience.
- Lead the design, implementation, and operation of cutting-edge ML Training and inference performance optimization techniques.
- Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
- Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.
BASIC QUALIFICATIONS
- Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
- Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
- Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.
- Proficient in Python and C++
- Experience with model compression techniques to reduce model size and improve performance.
PREFERRED QUALIFICATIONS
- 10+ years of total experience, including 4+ years of working on large-scale model training or inference platforms.
- Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
COMPENSATION
- Base Salary Range: $242,000 - $389,000 a year
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. Follow us on LinkedIn.
ACCOMMODATIONS
If you need an accommodation to participate in the application or interview process please reach out to [email protected] 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 ML Software Engineer Jobs at Zoox
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Get Access To All JobsTips for Finding ML Software Engineer Jobs at Zoox
Tailor your portfolio to autonomy-specific ML
Zoox evaluates ML candidates on perception, sensor fusion, and real-time inference work. Projects involving LiDAR processing, object detection, or on-device model optimization will read as directly relevant compared to general deep learning experience.
Confirm your visa type before applying
Zoox sponsors H-1B, E-3, TN, and F-1 OPT among others, but eligibility depends on your nationality and current status. Mismatches between your visa category and what a team is set up to process can delay or derail an otherwise strong offer.
Start OPT paperwork well before your program ends
USCIS recommends filing your EAD application at least 90 days before your OPT start date. At a robotics company like Zoox, onboarding timelines can shift with program milestones, so a work authorization gap during that window creates real risk.
Ask about LCA scope during the offer stage
Zoox ML engineers often rotate across teams working on different subsystems. A Labor Condition Application filed by DOL for one job site or role classification may not automatically cover reassignments, so clarify how your employer handles LCA amendments before signing.
Use Migrate Mate to filter for open ML roles at Zoox
Zoox posts ML Software Engineer positions across several subteams at different times. Use Migrate Mate to surface active openings filtered by visa type and role so you're applying to positions your sponsorship category is eligible for.
Prepare for technical screening tied to production constraints
Zoox interviews for ML roles with an emphasis on model efficiency and safety margins, not just benchmark accuracy. Reviewing inference optimization techniques and understanding how ML systems behave under distribution shift will strengthen your performance in technical rounds.
Frequently Asked Questions
Does Zoox sponsor H-1B visas for ML Software Engineers?
Yes, Zoox sponsors H-1B visas for ML Software Engineer roles. The H-1B is the most common route for non-Australian, non-Canadian international candidates in this field. Because the H-1B is subject to an annual lottery, timing matters. Zoox files petitions in April for an October 1 start, so your job search timeline should account for that cycle.
Which visa types are commonly used for ML Software Engineer roles at Zoox?
Zoox supports a wide range of work visa categories for ML Software Engineers, including H-1B, H-1B1 visa for Singaporean and Chilean nationals, E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals, F-1 OPT and CPT for students, J-1 visa for exchange visitors, and Green Card pathways via EB-2 and EB-3. The right category depends on your nationality, degree, and current immigration status.
How do I apply for ML Software Engineer jobs at Zoox?
Start by browsing open ML Software Engineer positions at Zoox through Migrate Mate, which lets you filter roles by visa type to confirm your category is eligible before you apply. Zoox's ML interviews typically include a technical screen focused on applied ML concepts, followed by system design and coding rounds. Having work authorization documents ready to discuss early in the process avoids surprises at the offer stage.
What qualifications does Zoox expect for ML Software Engineer candidates?
Zoox typically looks for a bachelor's degree or higher in computer science, electrical engineering, or a related field, combined with hands-on ML engineering experience. Candidates who can demonstrate work on real-time or safety-critical systems stand out. Familiarity with PyTorch or TensorFlow, experience deploying models to hardware, and exposure to sensor data pipelines are commonly referenced in job descriptions for this role.
How do I time a visa sponsorship process when joining Zoox as an ML Software Engineer?
Timeline depends on your visa category. H-1B petitions must be filed by April 1 for an October start, so an offer needs to be in place before that window. E-3 and TN applications can move faster since they're processed at consulates or ports of entry, often within a few weeks. F-1 OPT applications require a 90-day USCIS processing window, so coordinate with your DSO as soon as you have an anticipated start date.