Senior Machine Learning Engineer, Autonomy Validation at Zoox

Foster City, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, Robotics, TechnologyIndustries

Requirements

PhD in a relevant field and/or 5+ years of experience working with machine learning models and data science methodologies in an industry setting
Expertise in machine learning concepts, including model training, evaluation, and optimization
Strong programming skills in Python and experience with relevant machine learning libraries (e.g., PyTorch, TensorFlow, Jax)
Experience with large-scale data processing and distributed computing
Experience in robotics, autonomous vehicles, or a related field, with an understanding of challenges in perception, prediction, and planning
Proven ability to drive progress independently, lead technical projects, and apply critical thinking to solve practical problems
Excellent communication skills and the ability to work effectively with cross-functional teams

Responsibilities

Lead technical initiatives by applying modern machine learning, including advanced techniques like encoder-decoder models, to critical validation problems at the intersection of ML and data science, serving as a key contributor and tech lead on a small, focused team
Pioneer methods to improve model interpretability, bridging the gap between "black box" models and systems engineering to build trust and ensure safety
Extend and refine features and embedding space used by models to better identify and cluster interesting driving scenarios, leveraging understanding of the autonomous driving stack and first-principles thinking
Incorporate metrics and information on autonomous vehicle (AV) performance into the model to make risk predictions more accurate and relevant
Apply data science expertise to optimize models and sampling methodologies, including analyzing large datasets to identify patterns and critical insights for finding risky or valuable scenarios
Collaborate cross-functionally with system safety, data science, software, and fleet operations teams to understand needs and integrate improvements supporting validation efforts

Skills

Machine Learning

Encoder-Decoder Models

Model Interpretability

Feature Engineering

Embeddings

Data Science

Autonomous Driving

Fleet Logs

Synthetic Data

Scenario Clustering

Python

Zoox

Develops autonomous electric ride-hailing vehicles

About Zoox

Zoox focuses on creating a fully integrated autonomous ride-hailing service designed specifically for urban transportation. Unlike other companies that modify existing vehicles for self-driving capabilities, Zoox has engineered its own vehicle from the ground up, optimizing it for safety, efficiency, and passenger comfort. The vehicle features advanced sensors, cameras, and AI systems that allow it to navigate complex city environments. It can carry up to four passengers in a spacious interior, ensuring a pleasant ride experience. Safety is paramount, with rigorous testing and collaboration with regulatory bodies to meet high standards. Additionally, Zoox's vehicles are fully electric, promoting sustainability by reducing emissions. The company also develops a user-friendly ride-hailing platform that uses data analytics to improve routing and reduce wait times. Zoox aims to enhance urban mobility while prioritizing safety and environmental responsibility.

Menlo Park, CaliforniaHeadquarters

2014Year Founded

$1,206.2MTotal Funding

ACQUISITIONCompany Stage

Automotive & Transportation, Energy, AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Health Insurance

Maternity & Paternity Leave

Vacation & Paid Time Off

Sick Days

Free Lunch or Snacks

Employee Assitance Program

Risks

Increased competition from Waymo and Cruise may impact Zoox's market share.

Expansion into new cities introduces regulatory and operational challenges for Zoox.

Partnership with Williams Racing may divert focus from core vehicle development.

Differentiation

Zoox designs vehicles specifically for autonomous operation, unlike retrofitting existing cars.

Zoox's vehicles feature a unique, futuristic design with advanced AI systems.

Zoox offers a fully integrated ride-hailing service optimized for safety and efficiency.

Upsides

Zoox's expansion into Austin and Miami opens new markets and data collection opportunities.

Partnership with Williams Racing boosts Zoox's brand visibility in the U.S. market.

Hiring former Tesla executive Gao could accelerate Zoox's technological advancements.

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