Data Science Engineer Jobs at Zoox with Visa Sponsorship
Zoox builds autonomous vehicles from the ground up, and its Data Science Engineer roles sit at the intersection of robotics, perception, and large-scale machine learning infrastructure. Zoox has an established track record of sponsoring international talent across multiple visa categories for technical engineering functions.
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INTRODUCTION
The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Model Optimization & Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex models (LLMs, VLMs, or FMs) for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices.
ROLE AND RESPONSIBILITIES
- Optimize large-scale models (LLMs, VLMs) using advanced quantization (PTQ, QAT), mixed-precision inference workflows, and parameter-efficient fine-tuning (LoRA, QLoRA).
- Architect and implement model conversion and compilation pipelines using TensorRT and TensorRT-LLM for edge deployment.
- Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries.
- Write and optimize custom CUDA kernels and TensorRT Plugins to maximize memory bandwidth and minimize latency on AI accelerators.
- Write production-level, highly concurrent, and memory-safe C++ and Python code for real-time inference on vehicle SOCs.
BASIC QUALIFICATIONS
- Deep expertise in model quantization (PTQ, QAT) and mixed-precision inference workflows (INT8, FP8, INT4, BF16/FP16).
- Proven experience optimizing large-scale models (LLMs, VLMs, or VLAs) utilizing KV-cache optimization (e.g., PagedAttention), Speculative Decoding, and Efficient Attention mechanisms (FlashAttention, Linear Attention).
- Extensive experience with model conversion/compilation pipelines (TensorRT, TensorRT-LLM) and performing rigorous parity/latency benchmarking.
- Proficiency in low-level programming for AI accelerators, specifically writing and optimizing custom CUDA kernels and TensorRT Plugins.
- Production-level C++ (14/17/20) and Python programming skills, with experience writing concurrent, memory-safe, real-time inference code for edge devices.
PREFERRED QUALIFICATIONS
- Experience with distributed training pipelines and model/tensor parallelism (PyTorch Distributed, Ray, DeepSpeed, Megatron-LM) and runtime efficiency optimization for GPU clusters.
- Familiarity with autonomous driving perception stacks (temporal 3D object detection, BEV, 3D Occupancy Networks) and processing multi-modal sensor streams (Vision, LiDAR, Radar).
- Understanding of end-to-end autonomous driving paradigms (VLA models, closed-loop simulation validation).
COMPENSATION
- Base Salary Range: $242,000 - $290,000 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.
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
The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Model Optimization & Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex models (LLMs, VLMs, or FMs) for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices.
ROLE AND RESPONSIBILITIES
- Optimize large-scale models (LLMs, VLMs) using advanced quantization (PTQ, QAT), mixed-precision inference workflows, and parameter-efficient fine-tuning (LoRA, QLoRA).
- Architect and implement model conversion and compilation pipelines using TensorRT and TensorRT-LLM for edge deployment.
- Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries.
- Write and optimize custom CUDA kernels and TensorRT Plugins to maximize memory bandwidth and minimize latency on AI accelerators.
- Write production-level, highly concurrent, and memory-safe C++ and Python code for real-time inference on vehicle SOCs.
BASIC QUALIFICATIONS
- Deep expertise in model quantization (PTQ, QAT) and mixed-precision inference workflows (INT8, FP8, INT4, BF16/FP16).
- Proven experience optimizing large-scale models (LLMs, VLMs, or VLAs) utilizing KV-cache optimization (e.g., PagedAttention), Speculative Decoding, and Efficient Attention mechanisms (FlashAttention, Linear Attention).
- Extensive experience with model conversion/compilation pipelines (TensorRT, TensorRT-LLM) and performing rigorous parity/latency benchmarking.
- Proficiency in low-level programming for AI accelerators, specifically writing and optimizing custom CUDA kernels and TensorRT Plugins.
- Production-level C++ (14/17/20) and Python programming skills, with experience writing concurrent, memory-safe, real-time inference code for edge devices.
PREFERRED QUALIFICATIONS
- Experience with distributed training pipelines and model/tensor parallelism (PyTorch Distributed, Ray, DeepSpeed, Megatron-LM) and runtime efficiency optimization for GPU clusters.
- Familiarity with autonomous driving perception stacks (temporal 3D object detection, BEV, 3D Occupancy Networks) and processing multi-modal sensor streams (Vision, LiDAR, Radar).
- Understanding of end-to-end autonomous driving paradigms (VLA models, closed-loop simulation validation).
COMPENSATION
- Base Salary Range: $242,000 - $290,000 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.
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.
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Get Access To All JobsTips for Finding Data Science Engineer Jobs at Zoox Jobs
Align your portfolio to autonomy-specific ML problems
Zoox hires Data Science Engineers to work on perception, prediction, and planning systems. Projects involving sensor fusion, real-world robotics datasets, or simulation pipelines are far more relevant than general analytics or business intelligence work.
Time your OPT application to match Zoox hiring cycles
USCIS recommends filing OPT applications at least 90 days before your program end date. Zoox engineering hiring tends to accelerate in the first half of the calendar year, so an early OPT filing gives you maximum available work authorization when roles open.
Understand how PERM affects your long-term eligibility
For EB-2 and EB-3 Green Card sponsorship, your employer initiates PERM labor certification with DOL. Autonomous vehicle engineering roles frequently meet the definition of a specialty occupation, which strengthens the case for an employer willing to begin that process.
Target teams where your ML specialty matches open headcount
Zoox organizes Data Science Engineering around specific technical domains including prediction modeling, mapping, and safety validation. Applying to a team whose published research aligns with your background increases the likelihood of reaching hiring managers who can advocate for sponsorship internally.
Use Migrate Mate to find open Data Science Engineer roles at Zoox
Sponsorship-verified roles can be hard to identify on general job boards. Migrate Mate filters open positions at Zoox by visa type, so you can find Data Science Engineer openings that match your specific immigration situation before you apply.
Data Science Engineer at Zoox jobs are hiring across the US. Find yours.
Find Data Science Engineer at Zoox JobsFrequently Asked Questions
Does Zoox sponsor H-1B visas for Data Science Engineers?
Yes, Zoox sponsors H-1B visas for Data Science Engineers. The role qualifies as a specialty occupation under USCIS guidelines given the degree requirements in computer science, statistics, or a related engineering field. Because H-1B selection is subject to an annual lottery, many candidates at Zoox also explore the E-3 or TN categories if their nationality qualifies.
How do I apply for Data Science Engineer jobs at Zoox?
Applications go through Zoox's careers portal, where engineering roles are listed by team and technical domain. You can also browse sponsorship-verified Data Science Engineer openings at Zoox through Migrate Mate, which shows which positions are available and which visa types the company supports. Tailoring your application to Zoox's autonomy stack, particularly perception or prediction work, strengthens your submission significantly.
Which visa types does Zoox commonly use for Data Science Engineer roles?
Zoox sponsors H-1B and H-1B1 for most international Data Science Engineers, along with E-3 for Australian citizens and TN for Canadian and Mexican nationals whose roles appear on the USMCA qualifying occupation list. F-1 OPT and CPT are supported for students completing U.S. degrees, and Zoox also files EB-2 and EB-3 petitions for candidates pursuing permanent residence.
What qualifications does Zoox expect for Data Science Engineer roles?
Zoox Data Science Engineer roles typically require a bachelor's degree at minimum in computer science, electrical engineering, statistics, or a closely related field, with a master's or PhD common for senior positions. Practical experience with large-scale ML frameworks, Python-based data pipelines, and real-world dataset engineering is expected. Autonomous vehicle or robotics domain knowledge is a distinguishing factor in competitive candidate pools.
How do I think about the immigration timeline when targeting a role at Zoox?
If you're on F-1 OPT, file early enough through USCIS to have valid work authorization in place before your program ends. H-1B sponsorship requires your employer to register in the annual lottery each March, with employment starting October 1 at the earliest. E-3 and TN processing is faster, often resolved within weeks through consular processing, which makes them practical alternatives if you need to start sooner.
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