---
title: 'Manager - Model Evaluation at Zoox'
canonical: 'https://feeny.ai/job/manager-model-evaluation-zoox-foster-city-4s81ffwp6wwx'
type: 'job'
last_seen: '2026-09-15'
---

# Manager - Model Evaluation at Zoox

- **Company:** Zoox
- **Location:** Foster City, CA
- **Compensation:** $237k–$338k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-14
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.lever.co/zoox/8714ca37-74ad-4cf5-8f08-c80cd3df7215

## Job description

As the Manager of Model Validation & Verification (VnV) for Behavior Autonomy, you will lead an engineering and data science team responsible for evaluating, benchmarking, and validating the machine learning models and behavioral algorithms that drive our autonomous vehicle (AV) prediction and planning stacks.

You will own the statistical frameworks, offline/online evaluation metrics, and validation pipelines that ensure our behavioral models operate safely, comfortably, and predictably. Operating at the intersection of Data Science, Machine Learning, and Safety Engineering, you will partner closely with Autonomy Software, Prediction, Planner, and ML Operations teams to establish data driven release criteria for our AV fleet.

In this role, you will:

- Team Leadership & Execution: Lead, mentor, and scale a high-performing team of Data Scientists, ML Validation Engineers, and Software Engineers while driving roadmaps, sprint execution, resource allocation, and high-throughput model releases with rigorous safety guardrails. Culture of Rigor: Foster a culture of statistical excellence, healthy skepticism, proactive risk tracking, and data-driven decision-making.
- Validation Strategy & Methodologies: Define and execute end-to-end validation strategies across offline evaluation, open/closed-loop simulation, and shadow-mode fleet benchmarking to ensure robust behavioral model performance. Statistical uncertainties, and regressions into clear, data-driven recommendations for release gating and executive leadership.
- Metrics, Release Gating & Rigor: Oversee metric development and standardization with System Safety and Autonomy teams, establishing quantitative go/no-go release criteria for Behavioral Planner and Prediction ML models while fostering statistical rigor and proactive risk management.
- Cross-Functional & Infrastructure Partnership: Partner closely with Planner, Prediction, MLOps, and Developer Efficiency teams to translate behavioral requirements into measurable validation targets, streamline dataset and evaluation pipelines, and optimize runtime and compute costs.
- Executive Communication & Decision-Making: Translate complex model performance trade-offs, statistical uncertainty, regressions, and safety risks into clear, data-driven recommendations for release decisions and executive leadership.

Qualifications:

- Experience: Masters or PhD in CS, Robotics, Applied Statistics or a related field and 3+ years of direct engineering management experience leading Data Science, Machine Learning, or V&V engineering teams, alongside 7+ years of technical experience in robotics, autonomous systems, or AI/ML.
- Domain Knowledge: Strong background in ML model validation, behavioral evaluation frameworks, system-level performance benchmarking, and statistics.
- Software & Systems Literacy: Strong technical foundation in Python and modern data/ML platforms, with exposure to or conceptual literacy in large-scale production codebases (C++ or distributed systems). Proven ability to partner with systems software engineers, review technical architecture, and understand compute/performance trade-offs, Track record of leading teams evaluating complex robotic systems
- Technical Depth: Proven familiarity with modern C++/Python ML environments, simulation frameworks, high-throughput ML evaluation pipelines.
- Cross-Functional Leadership: Demonstrated ability to navigate complex organizational trade offs between release velocity, compute cost, and safety rigor.

Bonus Qualification:

- Experience with autonomous vehicles, robotics, or other safety-critical systems.
- Experience building large-scale simulation, model evaluation, or validation infrastructure.
- Experience with reinforcement learning, generative AI, or distributed ML systems.

## 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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