Senior AI Software Engineer Jobs at Zoox with Visa Sponsorship
Zoox builds autonomous vehicles from the ground up, and Senior AI Software Engineer roles sit at the core of that mission, spanning perception, planning, and prediction systems. Zoox has a consistent track record of sponsoring work visas across a range of categories, making it a realistic target for international engineers.
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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
In This Role, You Will
- 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
In This Role, You Will
- 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 Senior AI Software Engineer Jobs at Zoox Jobs
Align your portfolio to AV perception stacks
Zoox's AI roles concentrate on sensor fusion, motion planning, and learned prediction models. Before applying, restructure your project portfolio to lead with work on lidar, camera, or radar pipelines rather than general ML or NLP experience.
Verify E-Verify enrollment before your interview
Zoox participates in E-Verify, which is required for F-1 OPT STEM extension eligibility. Confirm enrollment status through the E-Verify employer search before accepting any offer, so your 24-month STEM extension timeline isn't at risk.
Target roles that specify real-time systems experience
Senior AI postings at Zoox frequently require experience with safety-critical, real-time inference. Roles scoped to embedded or on-vehicle AI are more likely to carry dedicated immigration support because the talent pool is narrower and the hire is harder to replace.
Build your case for an H-1B specialty occupation early
USCIS requires that H-1B roles demonstrate a direct connection between the job duties and a specific degree field. For AV engineering roles, document how your advanced degree in computer science, robotics, or electrical engineering maps to each technical responsibility listed in the job description.
Use Migrate Mate to filter Zoox openings by visa type
Zoox posts Senior AI Software Engineer roles across several sub-teams with different sponsorship scopes. Use Migrate Mate to filter active Zoox postings by the visa categories you need, so you're applying to positions already aligned with your work authorization situation.
Negotiate offer timing around H-1B cap deadlines
If you're cap-subject, USCIS opens H-1B registration in March for an October 1 start date. When Zoox extends an offer, ask your recruiter to confirm the intended filing date so your start date doesn't fall outside the approved petition period.
Senior AI Software Engineer at Zoox jobs are hiring across the US. Find yours.
Find Senior AI Software Engineer at Zoox JobsFrequently Asked Questions
Does Zoox sponsor H-1B visas for Senior AI Software Engineers?
Yes, Zoox sponsors H-1B visas for Senior AI Software Engineer roles. As an autonomous vehicle company competing for specialized AI talent, Zoox consistently files H-1B petitions for engineering positions that require expertise in areas like perception, motion planning, and on-vehicle inference. Sponsorship is standard practice for qualified candidates, not an exception.
Which visa types are commonly used for Senior AI Software Engineer roles at Zoox?
Senior AI Software Engineers at Zoox are commonly sponsored on H-1B visas, with E-3 available exclusively for Australian citizens and H-1B1 for Chilean and Singaporean nationals. F-1 OPT and STEM OPT are supported for recent graduates, and TN status applies for Canadian and Mexican engineers. Green Card sponsorship through EB-2 or EB-3 PERM is also available for longer-term employees.
How do I apply for Senior AI Software Engineer jobs at Zoox?
Browse open Senior AI Software Engineer positions at Zoox through Migrate Mate, which filters roles by visa sponsorship type so you can focus on postings aligned with your work authorization. Once you identify a match, apply directly through Zoox's careers portal. Tailor your resume to reflect autonomous systems experience, particularly in perception, planning, or prediction pipelines, since Zoox hiring teams look for domain-specific depth.
What qualifications does Zoox expect for Senior AI Software Engineer candidates?
Zoox typically expects a master's or PhD in computer science, robotics, or electrical engineering for Senior AI Software Engineer roles, along with hands-on experience building and deploying models in safety-critical or real-time environments. Proficiency in C++ or Python, experience with sensor data from lidar or cameras, and prior work on production-grade ML systems all strengthen your application significantly.
How do I think about visa processing timelines when targeting a role at Zoox?
If you're pursuing an H-1B and are cap-subject, USCIS registration opens in March and approved petitions take effect October 1, so plan for a gap of up to six months between an offer and your start date. F-1 STEM OPT extends your authorization by 24 months and lets you start immediately after graduation, making it a practical bridge while you await an H-1B selection.
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