
Provide mobility as a service.
Machine Learning Engineer Intern, Simulation
필수 스킬
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Machine Learning
Zoox’s internship program provides hands-on experiences with state of the art technology, mentorship from some of the industry's brightest minds, and the opportunity to play a part in our success. Internships at Zoox are reserved for those who demonstrate outstanding academic performance, activities outside their course work, aptitude, curiosity, and a passion for Zoox's mission.
The Simulation team creates high fidelity synthetic data for training and testing AV AI, as well as real time sensor data for hardware-in-the-loop simulation. Zoox vehicles are deployed in many cities across the US, and wherever Zoox goes, Simulation makes sure we are good to go.
As an MLE Intern working on Simulation, you may be assigned to one of the following teams:
On the 3D World Sim team, you will extend our simulation pipeline to reproduce dynamic actors accurately in simulation. You will research and evaluate various reconstruction algorithms and integrate the most promising of them into our simulation framework.
On the Agent Simulation team, you will develop and improve models that realistically simulate the behavior of other road agents like pedestrians and vehicles. You will leverage software engineering and machine learning skills to ensure these simulated agents exhibit a wide range of plausible and representative human behaviors, which is critical for validating the safety and performance of Zoox's autonomous driving technology.
On the 3D Sensor Simulation team, you will help create high fidelity synthetic data for training and testing AV AI, as well as real time sensor data for hardware-in-the-loop simulation. You will develop 3D ML models and training datasets for 3D sensor simulation using modern machine learning architectures. Collaborate with the Sensors, Perception, and Validation teams to evaluate and iteratively improve the fidelity of sensor simulation.
On the Scenario Authoring team, you will help create agentic AI systems capable of generating novel scenarios for validating the safety and performance of Zoox's autonomous driving technology. You will leverage your software engineering and machine learning skills to gather data, fine-tune existing diffusion / foundation models, add new capabilities to our LLM agent, and evaluate success against customer requirements.
On the Scenario Automation team, you will help build scenario generation and analysis tools used to evaluate robot behavior via simulation. You will leverage your software engineering and machine learning skills to recreate high-fidelity simulation scenarios from recorded real-world driving data. Together, we’re creating a highly-scalable system used by mission assurance and autonomy engineers to continuously improve the safety and reliability of our robots.
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Zoox 소개

Zoox
AcquiredProvide mobility as a service.
501-1,000
직원 수
Foster City
본사 위치
$1.3B
기업 가치
리뷰
10개 리뷰
3.7
10개 리뷰
워라밸
2.5
보상
3.8
문화
4.0
커리어
3.2
경영진
2.8
65%
지인 추천률
장점
Innovative and cutting-edge technology projects
Supportive and collaborative team environment
Good compensation and benefits
단점
Fast-paced work environment
Poor work-life balance and long hours
High stress levels and workload
연봉 정보
139개 데이터
Mid/L4
Senior/L5
Intern
Mid/L4 · Data Scientist
2개 리포트
$252,794
총 연봉
기본급
$194,457
주식
-
보너스
-
$249,600
$256,188
면접 후기
후기 3개
난이도
3.0
/ 5
소요 기간
14-28주
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Hiring Manager Interview
5
Final Interview Rounds
자주 나오는 질문
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Machine Learning Concepts
Data Analysis
최근 소식
Amazon’s Autonomous Car Has Arrived. Why Zoox Could Have a Rough Road Ahead. - MSN
MSN
News
·
2w ago
Texas continues to be a testing ground for self-driving car companies - Spectrum News
Spectrum News
News
·
3w ago
Amazon: Zoox Enters The Robo Taxi Race, Jassy On Growth And Anthropic Mythos - Seeking Alpha
Seeking Alpha
News
·
3w ago
Comments of the R Street Institute in RFC on Zoox Petition - R Street Institute
R Street Institute
News
·
3w ago