Senior Systems Engineer - Perception

Zoox

2600

Foster City, CA, United States

Posted on: 2018-06-21

Category: emobility

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Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

As a member of the Perception team, you will be part of the “eyes and ears” of the Zoox autonomous driving stack, deploying state-of-the-art AI solutions to ensure safe and effective driving. In this role you will be responsible for designing and building requirements and testing strategies for the Perception system. Your work will have a broad impact on shipping high performance ML models by ensuring we have comprehensive and robust evaluation pipelines to ensure safe and effective driving behavior. Think you have what it takes to build the best machine learning systems on the planet? Come join us!

Compensation

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $204,000-$256,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.

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. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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.

Responsibilities

Build large-scale validation and metrics systems using real world structured testing, state-of-the-art simulations, distributed computing, and modern data analysis technologies

Bridge the gap between systems engineering and state-of-the-art machine learning approaches by collaborating with partner teams, designing robust evaluation system architecture, building up scalable metrics/tools, and leading the verification and validation efforts at various levels of abstraction

Develop and evangelize our strategy for data development and model evaluation metrics to ensure safe and effective autonomous driving, including defining objective success criteria for ML model deployment

Analyze and interpret validation outcomes to provide recommendations to improve the performance of the ML models.

Define key performance metrics that will help Perception engineers to directly measure the impact of the new features they are developing on the end-to-end driving behavior.

Stay up-to-date with the latest developments in machine learning validation techniques and best practices for perception in autonomous vehicles.

Qualifications

Bachelor's, Master's or PhD in Robotics, electrical engineering, systems engineering or related fields

Domain experience working on autonomous vehicles

Experience with developing functional requirements driven software components

Experience designing and building evaluation systems for classical and deep-learning models, including linking standard model metrics to end-to-end system behavior and key business metrics

Strong understanding of statistical analysis, experimental design, and hypothesis testing, including parametrics & non-parametric testing

Fluent with Python-based data and statistics frameworks, e.g. numpy, scipy, pandas, statsmodels and data visualization tools, e.g. matplotlib, seaborn, plotly

Experience with data query languages and common databases, e.g. SQL, NoSQL, Databases

Bonus Qualifications

Experience with automation functional safety standard such as ISO 21448, ISO26262, ASIL, DO-178B/C, etc

Have performed hazard analysis using one or more of the following methods: System Theoretic Process Analysis (STPA), qualitative or quantitative Fault Tree Analysis (FTA), Failure Modes and Effects Analysis (FMEA), Hazard and Operability Analysis (HAZOP), Functional Hazard Analysis (FHA), etc

Experience on the AI stack components of an autonomous vehicle, such as perception, prediction and planner modules

Experience building or evaluating ML models that operate on raw sensor data (detection, classification, tracking, etc.)

Experience handling big data, including exposure to distributed data and/or compute, e.g. Hadoop, Spark, Hive, MapReduce, Databricks

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