Skyrocket Ventures is a recruiting firm for hundreds of high growth technology companies that range from industry leaders to top-tier startups. This opportunity is with one of our client companies for a full-time permanent hire. Please only apply if you are authorized to work in the U.S.
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Backend Engineer - Autonomous Vehicle Startup, learn and use Go / Golang
Redwood City, CA
This company is a top tier autonomous vehicle startup that is disrupting a trillion dollar industry that touches billions of people. The team is comprised of industry veterans with expertise in autonomous vehicles, robotics, computer vision, augmented reality, and machine learning.
The company will pay very competitive salary (up to $180k) plus equity which could be very lucrative.
- The technology stack includes Go, AWS, C++, Docker, React, and WebRTC. This job would be primarily using Go and AWS.
- Building cloud infrastructure that will coordinate a fleet of autonomous vehicles.
- Making important architectural decisions regarding cloud infrastructure for vehicle monitoring, teleoperation, and data warehousing of the sensor data.
- Collaborating with domain experts in deep learning to facilitate learning of statistical models from the vehicle sensor data.
- Working closely with a team of hardware and software engineers to build autonomous vehicles.
- Expertise in at least one programming language such as Go, C++, C, Java, Python, Scala, etc.
- Interest/ability to learn and primarily use Go / Golang
At least 3 years of experience in backend application development
- At least 3 years experience with at least one of AWS, GCP, or Azure
- Has experienced web development at scale
- Desire to work in a fast-paced software engineering environment
Nice to have:
- Experience building applications in Go / Golang
- Experience using AWS
- Experience building cloud infrastructure that interfaces with IoT or hardware devices
- Experience building applications using WebRTC
- Experience with Docker
- Experience building projects from an early stage
- Experience with infrastructure and data warehousing that supports large-scale statistical learning
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