The role
At Zoox, we have set the goal to provide our customers with the highest level of safety while using our fully autonomous vehicles. You will work with a team of world-class engineers with diverse backgrounds such as robotics, controls, simulation, and vehicle engineering to enable our vehicle to deliver outstanding energy efficiency and range in service. Operating a fleet of robotaxis at scale requires balancing performance, cost, and energy usage at the time - in this position, you will spearhead energy management and energy-efficient architectures across the vehicle platform and robotaxi fleet. You’ll collaborate on electrical powertrains, high-voltage batteries, thermal architectures, and low-voltage systems, as well as the sophisticated compute and sensing suites required for autonomous operation.
In this role, you will:
- Develop holistic engineering and product strategies for vehicle energy management.
- Develop energy budgets, energy saving features, and software controls strategies across sub-systems.
- Work closely with simulation engineers to develop digital vehicle models for energy consumption prediction and vehicle design optimization across drive cycles.
- Integrate those models into larger end to end simulations to analyze fleet wide energy performance for service operations.
- Advocate for energy efficiency as vehicle development progresses - you’ll need passion and backbone to deliver results and make data-driven tradeoffs on behalf of energy.
Qualifications
- Bachelor’s degree in engineering, physics, or a related technical field
- 7+ years of direct experience in system design and energy management in vehicular or robotics domains
- Familiarity with design optimization processes, including multi-disciplinary analysis and optimization
- Experience working with business and product stakeholders on translating business objective into engineering requirements
Bonus Qualifications
- Master’s degree in engineering, physics, or related technical field
- Expertise with at least one programming language - Python and/or C++ preferred
- Experience with EV charging infrastructure and hardware