Sr. Software Engineer, Backend

Carbon Robotics Carbon Robotics · Robotics · Carbon Robotics, Corporate · Software Engineering

Senior Backend Software Engineer to build and scale cloud and on-prem infrastructure software supporting AI and robotics products, specifically focusing on the LaserWeeder solution. The role involves developing services for a machine learning model training pipeline and providing remote monitoring for a global fleet of robots.

What you'd actually do

  1. Partner with Engineering teams to build and scale cloud and on-prem infrastructure software to support our revolutionary Laser Weeding solution and future products.
  2. Quickly build and troubleshoot applications and tooling to support a dynamic and continuous machine learning model training pipeline with ownership and collaboration
  3. What you will build will provide remote monitoring and visibility to our fleet of Robots located around the globe.
  4. Drive decision through project planning, task delegation and leading problem solving efforts to reiterate quickly

Skills

Required

  • 5+ years of professional experience
  • developing and deploying distributed systems and services
  • Golang or Python
  • minimum of 2 years using Golang
  • Proficiency with relational databases (Postgres/MySQL/Sqlite)
  • Proficiency with web services (REST/GRPC)
  • AWS or other similar cloud providers
  • General knowledge of Linux, Docker, and networking concepts

Nice to have

  • experience with non-relational databases
  • Exposure to Deep Learning Pipelines
  • expertise in building and testing code with clear interfaces and isolation
  • Effective verbal and written communication skills
  • desire to work in multidisciplinary teams
  • BS+ in Computer Science, Computer Engineering or related field (or equivalent experience)

What the JD emphasized

  • do whatever it takes
  • ensure our customers have reliable and safe products

Other signals

  • AI/ML is core to the product
  • Robotics product
  • Cloud and on-prem infrastructure software
  • ML model training pipeline
  • Fleet of Robots monitoring