Job Description
Our Ride and Fleet Backend team is looking for a Software Engineer to build out the Fleet Dispatch System to efficiently dispatch missions to our robots. Zoox robots take missions like Rideshare Trips, Charging, Cleaning, Return to Depot, R&D missions, and Roaming missions. It is the backbone of our autonomous fleet management system and the brains behind connecting our riders and vehicle operators to our robots!
Qualification
- Bachelor’s/Master’s degree in Computer Science, Engineering, Mathematics, Operations Research, or related field.
- Proven experience in algorithm development, with a strong emphasis on operational research methodologies.
- Proficiency in programming languages like Python, Java or Kotlin, or C++.
- Solid background in machine learning, AI, operational research, and data analysis.
- Passion for learning new technologies, domains, and challenging the status quo.
- Strong mathematics skills.
- Exceptional problem-solving, analytical, and quantitative skills.
Bonus Qualification
- PhD in Operations Research, Computer Science, or a related field with a focus on optimization algorithms or AI.
- Experience with GIS and mapping software.
- Experience in transportation, logistics, or autonomous vehicles.
- Experience in building/using fleet simulation tools.
- Ability to lead through ambiguity and work with diverse stakeholders.
- Ability to Iterate quickly and efficiently on building end-to-end experiences.
- Experience handling large data sets and scaling service horizontally to a large number of users.
- Experience developing cloud services and an understanding of design for scalability, performance and reliability.
- Knowledge about microservice design patterns and DB access.
- Knowledge of engineering practices and patterns for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and live site operations.
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.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] 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.
Requirements
Qualification
- Bachelor’s/Master’s degree in Computer Science, Engineering, Mathematics, Operations Research, or related field.
- Proven experience in algorithm development, with a strong emphasis on operational research methodologies.
- Proficiency in programming languages like Python, Java or Kotlin, or C++.
- Solid background in machine learning, AI, operational research, and data analysis.
- Passion for learning new technologies, domains, and challenging the status quo.
- Strong mathematics skills.
- Exceptional problem-solving, analytical, and quantitative skills.
Bonus Qualification
- PhD in Operations Research, Computer Science, or a related field with a focus on optimization algorithms or AI.
- Experience with GIS and mapping software.
- Experience in transportation, logistics, or autonomous vehicles.
- Experience in building/using fleet simulation tools.
- Ability to lead through ambiguity and work with diverse stakeholders.
- Ability to Iterate quickly and efficiently on building end-to-end experiences.
- Experience handling large data sets and scaling service horizontally to a large number of users.
- Experience developing cloud services and an understanding of design for scalability, performance and reliability.
- Knowledge about microservice design patterns and DB access.
- Knowledge of engineering practices and patterns for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and live site operations.
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