Senior Software Engineer
Machine Learning Platform
Confirmed live in the last 24 hours
Facet

11-50 employees

Content-aware image editing software
Company Overview
Facet’s mission is to redefine and humanize the creative process by helping a new generation of artists explore new vectors of expression as they work in concert with the state-of-the-art in generative AI. The company enables artists to experiment and iterate through creative spaces faster and more seamlessly with AI visual creative tools that blend machine perception with cutting edge graphics.
AI & Machine Learning

Company Stage

Series A

Total Funding

$17M

Founded

2017

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

20%

2 year growth

100%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Terraform
CategoriesNew
Backend Engineering
Full-Stack Engineering
Software Engineering
Requirements
  • 5+ years of experience developing backend infrastructure / services
  • Experience with Infrastructure as Code tools such as Terraform
  • Deep knowledge of industry ecosystems around build, deployment, orchestration, and monitoring
  • Ability to operate at pace and make decisions quickly applying judgement to balance pace, rigor and risk
  • Committed to delivering outcomes, overcoming challenges, focusing on what matters, and execution
  • Demonstrated ability to propose effective solutions, build them quickly, and iterate on them in response to feedback
  • Aptitude for clearly communicating difficult technical concepts
  • Familiarity with more than one cloud computing environment
  • Empathy for the designers, artists, and the visual creative workers who use our product
Responsibilities
  • Enable the Facet team to easily develop and deploy new machine learning capabilities at scale
  • Be ruthless about latency and performance; Facet is integral to our users’ professional work
  • Design, develop, document and test the infrastructure that hosts Facet’s ML services
  • Work closely with engineers, product, and other domain experts to productionize AI/ML models and pipelines
  • Instrument and monitor the health of ML services and the quality of the results they produce
  • Stay up to date on the latest leading technologies in the AI/ML software ecosystem