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Mid-Senior Platform Engineer (Go, NLP, API) at LoopVOC

🕑 Posted 167 days ago

About this job

Job type: Contract
Experience level: Mid-Level, Senior
Role: Data Scientist, DevOps
Industry: B2B, Data & Analytics, SaaS
Company size: 1–10 people
Company type: Private

Technologies

go, kubernetes, istio, docker, machine-learning

Job description

LoopVOC is looking for a talented and motivated platform engineer who can hit the ground running and support taking our NLP product to the next level under a 100% remote work environment. Our software is designed to revolutionize the way SaaS companies collect, analyze, and respond to feedback from their customers, by combining text analytics with a simple user experience. We're seeking someone to help us expand and scale our platform. This position will have software and infrastructure responsibilities, from building new features and integrations to making fundamental architecture choices to facilitating continuous integration and deployment across the company. If this excites you, we’d love to hear from you!

Ideal candidate

  • You embrace and live a growth mindset
  • You work well independently, and with others and efficiently
  • You’ve used a combination of Go, Java, C, or Python to create fast, maintainable production software.
  • You know what it takes to scale a SaaS application deployed in a cloud environment
  • You're a creative problem solver
  • You’re a pro at designing and consuming RESTful APIs.
  • Familiarity with, if not an avid engineer, of working under a test-driven development process

Extra Points:

  • You’ve worked in the B2B SaaS or analytics space.
  • You’ve built tools with machine learning and natural language processing.
  • You know the following about Go right now without searching the internet: What is a channel and a go routine and how do they relate, What is an interface and why you should use them, How does a slice allocate memory as you append items to it, When a go binary is run what is the order of functions that are called in which packages.
  • You understand containerization of all your deployments in Docker and best practices for auto-scaling and load balancing your production environment in Kubernetes