AI Data Engineer Jobs at Zoox with Visa Sponsorship
Zoox builds autonomous vehicles from the ground up, and AI Data Engineer roles sit at the core of that mission, turning raw sensor and simulation data into the training pipelines that teach cars to drive. Zoox has a broad, established sponsorship track record across multiple visa categories for engineering talent.
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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 AI Data Engineer Jobs at Zoox Jobs
Align your portfolio to AV data pipelines
Zoox's AI Data Engineers work on sensor fusion, labeling infrastructure, and large-scale ML training datasets. Before applying, build or document examples involving lidar, camera, or radar data processing. Generic ML portfolios won't stand out here.
Target teams building simulation and labeling tooling
Zoox posts AI Data Engineer roles across both real-world data ops and simulation pipeline teams. Identifying which sub-team aligns with your background lets you tailor your application and speak directly to their data infrastructure challenges in interviews.
Confirm your visa category before the offer stage
Zoox sponsors multiple nonimmigrant categories, including H-1B, E-3, TN, and F-1 OPT. Clarify which category applies to your situation before you receive a written offer, since each category has different filing timelines and employer obligations that affect your start date.
Use Migrate Mate to find open AI Data Engineer roles at Zoox
Job listings for specialized roles like AI Data Engineer move fast at autonomous vehicle companies. Search Migrate Mate to filter for open positions at Zoox that explicitly support visa sponsorship, so you're applying to roles confirmed to be accessible to international candidates.
Get your STEM credentials assessed before the H-1B petition
Zoox's AI Data Engineer roles require a specialty occupation determination from USCIS. If your degree is from outside the U.S. or in a field adjacent to computer science, get a formal credential evaluation from a NACES-approved agency before your employer files the I-129 petition.
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Find AI Data Engineer at Zoox JobsFrequently Asked Questions
Does Zoox sponsor H-1B visas for AI Data Engineers?
Yes, Zoox sponsors H-1B visas for AI Data Engineer roles. Because these positions require specialized knowledge in machine learning infrastructure, data pipelines, or autonomous systems, they typically meet USCIS's specialty occupation standard. Your employer files the H-1B petition on your behalf using Form I-129, and sponsorship is subject to the annual cap and lottery unless you qualify for a cap-exempt route.
Which visa types are commonly used for AI Data Engineer roles at Zoox?
Zoox supports a broad range of visa categories for engineering roles, including H-1B, H-1B1, E-3, TN, F-1 OPT, F-1 CPT, J-1, and Green Card pathways such as EB-2 and EB-3. F-1 OPT and CPT are common entry points for recent graduates, while H-1B and E-3 are standard for longer-term employment. The right category depends on your nationality, education, and where you are in your career.
What qualifications are expected for AI Data Engineer positions at Zoox?
Zoox typically looks for a bachelor's or master's degree in computer science, data engineering, or a closely related field, combined with hands-on experience building large-scale data pipelines, ML training infrastructure, or labeling systems. Familiarity with sensor data formats and autonomous vehicle datasets is a strong differentiator. For H-1B purposes, your degree must directly relate to the duties of the role, which Zoox and their immigration counsel will assess.
How do I apply for AI Data Engineer jobs at Zoox?
Start by browsing open AI Data Engineer roles through Migrate Mate, which filters for positions at Zoox that support visa sponsorship. Once you identify a role, apply directly through Zoox's careers portal. Tailor your resume to highlight data pipeline architecture, ML infrastructure, or AV data experience. If you're on a time-sensitive visa status like OPT, note your authorization end date clearly during the process to allow Zoox's recruiting and immigration teams enough lead time.
How do I think about timing if I need Zoox to file an H-1B for me?
The H-1B cap lottery registration opens each March for an October 1 start date. If you're hired after the lottery closes, your earliest cap-subject H-1B start date is the following October. If you're on OPT with a STEM extension, you may have enough runway to bridge the gap. Discuss your timeline with Zoox's immigration team early in the offer process so filing deadlines don't create a gap in your work authorization.
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