The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.
As a Machine Learning and System Optimization Engineer you will orchestrate and allocate overall system capacity to various core perception models running on-bot as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another.
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 compressing accelerating and deploying complex models including LLMs VLMs or foundation models for power- and thermal-constrained vehicle SoCs.
In addition you will optimize ML models write custom CUDA kernels and build highly concurrent inference code to ensure real-time deterministic execution on edge devices.
In this role you will:
Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot.
Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies.
Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
Write production-level low-latency and memory-safe C and CUDA code for real-time inference on vehicle systems.
Qualifications:
Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput.
Deep expertise in working with real-time systems & required constraints such as processing latency memory utilization and memory bandwidth pressure.
Deep expertise in model quantization (PTQ QAT) and mixed-precision inference frameworks (INT8 FP8 FP4 BF16/FP16).
Proficiency in low-level programming for AI accelerators specifically developing and optimizing custom ML OPs and TensorRT Plugins with efficient CUDA kernel implementations.
Production-level C (14/17/20) and Python programming skills with experience developing concurrent memory-safe real-time inference code for edge devices.
Bonus Qualifications:
Prior experience in high-performance robotics applications such as AV/drones/robots.
Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection BEV 3D Occupancy Networks) and multi-modal sensor processing (Vision LiDAR Radar).
Experience with end-to-end autonomous driving paradigms (VLM/VLA models Foundation models) and edge deployment technologies (e.g. TensorRT-LLM).
$226000 - $307000 a year
Base Salary Range
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 candidates 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. Were looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.
Required Experience:
Staff IC
The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.As a Machine Learning and System Optimization Engineer you will orchestrate and allocate overall system capacity to various core perception models run...
The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.
As a Machine Learning and System Optimization Engineer you will orchestrate and allocate overall system capacity to various core perception models running on-bot as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another.
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 compressing accelerating and deploying complex models including LLMs VLMs or foundation models for power- and thermal-constrained vehicle SoCs.
In addition you will optimize ML models write custom CUDA kernels and build highly concurrent inference code to ensure real-time deterministic execution on edge devices.
In this role you will:
Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot.
Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies.
Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
Write production-level low-latency and memory-safe C and CUDA code for real-time inference on vehicle systems.
Qualifications:
Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput.
Deep expertise in working with real-time systems & required constraints such as processing latency memory utilization and memory bandwidth pressure.
Deep expertise in model quantization (PTQ QAT) and mixed-precision inference frameworks (INT8 FP8 FP4 BF16/FP16).
Proficiency in low-level programming for AI accelerators specifically developing and optimizing custom ML OPs and TensorRT Plugins with efficient CUDA kernel implementations.
Production-level C (14/17/20) and Python programming skills with experience developing concurrent memory-safe real-time inference code for edge devices.
Bonus Qualifications:
Prior experience in high-performance robotics applications such as AV/drones/robots.
Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection BEV 3D Occupancy Networks) and multi-modal sensor processing (Vision LiDAR Radar).
Experience with end-to-end autonomous driving paradigms (VLM/VLA models Foundation models) and edge deployment technologies (e.g. TensorRT-LLM).
$226000 - $307000 a year
Base Salary Range
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 candidates 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. Were looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.
We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable for everyone. This is on-demand autonomous ride-hailing.
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