---
title: 'Senior/Staff Software Engineer, ML Training Optimization at Zoox'
canonical: 'https://feeny.ai/job/senior-staff-software-engineer-ml-training-optimization-zoox-foster-city-d1cj1c7qxsbj'
type: 'job'
last_seen: '2026-10-20'
---

# Senior/Staff Software Engineer, ML Training Optimization at Zoox

- **Company:** Zoox
- **Location:** Foster City, CA
- **Compensation:** $254k–$350k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-16
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.lever.co/zoox/2ae1f38f-1b7e-4ec1-8a20-cc3816f96878

## Job description

Zoox is on a mission to reimagine transportation and build ground-up autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We’re still early in deploying on public roads, so this is a great time to join and have a significant impact. The ML Platform team enables innovation in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The OpportunityAre you excited to own ML training optimization at Zoox and make the models that power autonomous driving train faster, cheaper, and at greater scale? You’ll set technical direction for distributed training, parallelism strategies, mixed-precision training, and RL on SOTA accelerators, especially for multi-modal VLA and VLM models. You’ll partner with all Autonomy teams (Perception, Prediction, Planner, Simulation, Collision Avoidance) and act as a force multiplier for our internal customers, while mentoring engineers and shaping the team’s roadmap as we expand into new ML domains. If you want to learn more about our stack behind autonomous driving, please lookhere. If you want to learn more about our ML Infrastructure, here is one of ourpast talks at re:Invent.

In this role, you will:

- Lead the design, implementation, and operation of training performance optimizations (data/tensor/pipeline parallelism, mixed precision, gradient checkpointing, GPU kernels) to scale VLM, VLA, and Foundation model training.
- Own the technical strategy and multi-quarter roadmap for RL framework and RL performance optimization for driving foundation models.
- Drive profiling and root-cause analysis of throughput bottlenecks across the compute, compiler, framework, and cluster-networking stack.
- Partner with ML researchers, data engineers, and hardware engineers to define requirements and make architectural decisions for large-scale training infrastructure.
- Build custom kernels and benchmarks that track and validate performance gains across the stack.
- Mentor engineers and raise the team’s technical bar through design reviews and best practices.

## Qualifications

Note: You do not have to meet all the requirements below to be considered for this position:

- 7+ years of total experience, including 4+ years on large-scale model training platforms, with a record of leading projects end to end.
- Deep experience with distributed training frameworks (Megatron-LM, TorchTitan) and efficiently utilizing GPU/accelerator clusters at scale.
- Experience with RL frameworks (Verl/MILES) and algorithms (GRPO, PPO).
- Experience with collective communication libraries (e.g., NCCL) and optimizing communication/compute overlap in multi-node training.
- Strong command of profiling tools (NVIDIA Nsight, PyTorch Profiler, or XLA/JAX profiling) to find and resolve training bottlenecks.
- Proficiency in Python or C++.
- Experience with ML compilers, performance tooling, or hardware/software co-design (GPU/TPU/accelerator architectures).
- Ability to influence across teams and communicate technical tradeoffs to both researchers and engineers.

## 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 accommodations@zoox.com 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.

## About Zoox

## Company Overview
- **One-liner**: Zoox is building a fully autonomous, all-electric, purpose-built robotaxi service to give the world a better way to ride.
- **Entity Type**: Private (independent subsidiary of Amazon, acquired in 2020)
- **Headquarters**: Foster City, California, USA (with offices in Las Vegas, San Francisco, Austin, Miami, Atlanta, Los Angeles)
- **Founded**: 2014
- **Founders**: Not specified in provided sources

## Core Business
- **Primary industry**: Autonomous ride‑hailing / Self‑driving electric vehicles
- **Target customers**: B2C – individual riders seeking safe, convenient, and sustainable urban transportation
- **Mission**: “Give the world a better way to ride” – providing safer, cleaner, autonomous ride‑hailing for everyone [zoox.com](https://zoox.com/about)

## Products & Services
- **Zoox Robotaxi**: A purpose‑built, fully autonomous electric vehicle designed from the ground up for ride‑hailing. Features bidirectional driving, four‑wheel steering, and no steering wheel or pedals. The service handles all charging, maintenance, and fleet management – riders simply get in and enjoy the ride [zoox.com](https://zoox.com).

## Market Standing
- **Valuation / Market Cap**: Not disclosed (Zoox is a private subsidiary of Amazon)
- **Key Metric**: Not publicly available (revenue and funding details are not reported as a stand‑alone entity)
- **Notable Investors / Partners**: Amazon (parent company)
- **Growth Signals**:
  - Received authorization from the Nevada DMV to operate robotaxis on public roads [zoox.com/about](https://zoox.com/about)
  - Expanded testing and operations to Las Vegas, Seattle, San Francisco, and other cities
  - Continues to scale its engineering and operations teams (multiple open roles on the careers page as of 2026)

## Competitive Advantages
- **Purpose‑built design**: Unlike retrofitted vehicles, Zoox’s robotaxi is designed from scratch for autonomous ride‑hailing (symmetrical, bidirectional, four‑wheel steering, no driver controls)
- **Amazon backing**: Deep financial resources, supply chain expertise, and cloud infrastructure (AWS) support rapid development and scaling
- **Full‑stack autonomy**: In‑house AI, computer vision, and sensing stack integrated directly into the vehicle design
- **Safety‑first approach**: Comprehensive testing, safety‑critical system design, and focus on public road validation

## Strategic Focus
- Achieving commercial launch of the Zoox ride‑hailing service in select U.S. cities
- Continuing to mature the autonomous driving system through real‑world testing and simulation
- Expanding the “Go‑to‑Market” strategy and building out operations teams (see CRM Lead, Go‑to‑Market Manager roles) [jobs.lever.co/zoox](https://jobs.lever.co/zoox)
- Scaling manufacturing and prototyping to prepare for fleet deployment

## Why Work Here
- **Culture**: Diverse, supportive community with inclusion‑focused strategy. Crew‑led groups for personal and professional development. Emphasis on trust, humility, and openness [zoox.com/careers](https://zoox.com/careers)
- **Work environment**: Hybrid? The careers page lists many roles as “On‑site” in Foster City, CA, with other office locations available. In‑office perks include a famous food program with daily changing local and sustainable dishes, plus a busy calendar of events and sports teams.
- **Benefits**: Comprehensive health plans (Cigna), mental health support, wellbeing program, flexible time off, generous family planning and caregiver support, and a commitment to work‑life balance.
- **Growth opportunities**: Work on cutting‑edge autonomous vehicle technology alongside some of the brightest minds in AI, engineering, computer vision, and more. Offers internships and re‑entry programs (via Path Forward) for career returners.
- **Recruitment process**: Uses AI tools to assist in reviewing applications but final decisions are human. No fees are charged at any stage – watch for recruitment scams [zoox.com/journal/landing-a-job-zoox](https://zoox.com/journal/landing-a-job-zoox)

## Sources
1. [Zoox official website](https://zoox.com)
2. [Zoox About page](https://zoox.com/about)
3. [Zoox Careers page](https://zoox.com/careers)
4. [Zoox job openings on Lever](https://jobs.lever.co/zoox)
5. [Zoox hiring and interview process](https://zoox.com/journal/landing-a-job-zoox)

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