Software Engineer - Calibration

Foster City, CA

Zoox

Zoox is reinventing personal transportation with an all-electric, fully autonomous ride-hail vehicle, built for riders, not drivers.

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Our Calibration, Localization, and Mapping (CLAMS) team is responsible for building the algorithms and tools necessary for keeping Zoox vehicles well calibrated, always knowing where they’re located within the world, and aware of their environment. Without precise calibration, localization, and mapping our vehicles would be at a disadvantage when it comes to perceiving and reasoning about the surrounding world, and is therefore foundational in enabling results from many other teams across Zoox. This work is critical for scaling autonomous driving in a safe and reliable way. We are looking for engineers who are ambitious and excited about helping Zoox deliver on its goals to deliver autonomous mobility.

In this role, you will

  • Develop nonlinear optimization algorithms to estimate relationships between different visual, depth, and motion sensing modalities.
  • Implement and validate cutting edge sensor calibration methodologies in a massively distributed computing environment.
  • Fuse various environmental observations into 360 degree positional/motion point clouds
  • Build reliable and fast calibration software and tools; your work will affect the entire vehicle fleet, every day.
  • Develop real-time on-vehicle calibration monitoring processes and metrics to ensure that our vehicles always operate with the best possible sensor calibration.

Qualifications

  • Bachelors in Computer Science or related field
  • At least 4 years of industry experience developing software
  • Mathematical/analytical skills (linear algebra, least square optimizations, multi-view geometry, estimation theory)
  • Experience with SLAM (ability to understand and set up the problem based on different modalities and constraints)
  • Fluency in C++ (experience in developing, troubleshooting, and deploying sophisticated computational algorithms)

Bonus Qualifications

  • Experience in characterizing and calibrating sensors such as cameras, stereo, TOF, Lidars, IMUs. 
  • Experience with spatial data structures
  • Proficiency in stochastic processes / probabilistic filters  
CompensationThere 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 $160,000 to $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 ZooxZoox 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.
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AccommodationsIf 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.
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Category: Engineering Jobs

Tags: Autonomous Driving Computer Science Linear algebra Machine Learning Robotics SLAM

Perks/benefits: Career development Equity / stock options Health care Insurance Salary bonus Signing bonus

Region: North America
Country: United States

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