CARMERA is a spatial AI company, built on the revolution of vehicular crowdsourcing and remote sensing to capture street-level change at global breadth and high definition depth. Our mission is to power the world’s leading road intelligence platforms to deliver safe autonomy and mobility for all. To deliver on this mission, we need an exceptional backend engineer to help lead scaling our Real Time Events (RTE) project.
Real Time Events is one of the most visible projects at CARMERA and is in need of a backend engineer who is eager to tackle scaling and mapping challenges. In this role you will have significant technical ownership and your contributions will have a measurable impact towards CARMERA’s goals. We are looking for someone who enjoys building iteratively, even before the perfect, well-defined solution reveals itself, and is energized by novel problems that require innovative solutions. We are excited to add to our talented team, and will strive to provide a challenging, and rewarding, experience!
- Design and build backend systems (in Python) that power CARMERA’s Real Time Events (RTE) and help lead our scaling efforts.
- Work with vehicular-generated, real-time sensor data.
- Work with a wide range of systems, processes and technologies to own and solve problems from end-to-end.
- Debug production issues across services at multiple levels of the stack, and maintain comprehensive unit test suites.
- Design, build and maintain scalable APIs for customers to consume mapping and event data.
We’d love to hear from you if:
- You are an Explorer, always learning, adapting and taking challenges head on with a positive and collaborative attitude.
- You can confidently contribute stand-alone, high quality code and have a history of regular contribution to a production product.
- You have implemented or contributed to RESTful APIs.
- You have relational database experience (we primarily use PostgreSQL).
- You have demonstrated professional experience writing comprehensive unit tests.
- You have high adaptability and flexibility -- you can work cross-functionally, and manage deadline pressure, ambiguity, and change.
- You have been successful in driving design and implementation of backend data processing systems for an evolving product.
- You feel energized by a fast-paced startup environment where project priorities change frequently - optimizationing, improving, iterating and implementing.
Strong preference (not required) if:
- You have strong coding skills in Python 3.
- You have geospatial or mapping experience or have worked with relational databases with geospatial extensions or purpose built geospatial datastores (ex. PostGIS).
- You have experience or a general understanding of DevOps (Docker, deploying infrastructure to AWS, etc).
- You have experience with big data and NoSQL datastores.
- Work on groundbreaking civic challenges cutting across some of the most meaningful innovations of this era, including autonomy, smart cities, IoT, big data and AI
- Be a foundational part of an exceptional, close-knit team who have diverse backgrounds and embrace challenges that are hard but achievable
- Attractive cash and equity compensation package
- Generous benefits package including premium health care plan, free cell phone plans and more
- Currently we're all working remotely, but even before transitioning to WFH, we embraced flexible working norms and time-off
- Generous paid parental leave
- Short-term Disability Insurance, Life/AD&D Insurance, Supplemental Disability Insurance
INSIDER TIP: Want to elevate your application to the top? A well articulated response to the question about related experience is the best way to guarantee an interview.
*This position is open to applicants currently residing in the continental U.S.*
We are an equal opportunity employer and diversity is critical to our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are advocates for justice and overt promoters of marginalized, under-represented groups and individuals.