Senior Software Engineer, Machine Learning Applications


San Francisco, CA, US
  • Job Type: Full-Time
  • Function: Engineering Software
  • Post Date: 03/18/2021
  • Website:
  • Company Address: , San Francisco, CA

About Planet

Planet is the leading provider of global, near-daily satellite imagery data and insights. Planet is driven by a mission to image all of Earth’s landmass every day, and make global change visible, accessible and actionable. Founded in 2010 by three NASA scientists, Planet designs, builds, and operates the largest fleet of satellites, as well as online software, tools and analytics needed to deliver data to users. Decision makers in business, government, and within organizations can use Planet's data and machine learning-powered analytics to develop new technologies, drive revenue, power research, and make informed, timely decisions to solve our world's toughest challenges.

Job Description

Welcome to Planet. We believe in using space to help life on Earth.

Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.

Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles.

As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.

We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.

Planet is headquartered in San Francisco, California, Earth.

About the Role:  

The Analytics Applications team at Planet is seeking an experienced software engineer to help us build web applications and data infrastructure for building the next generations of our machine learning products that derive insights from our global imagery. Our team is responsible for the APIs and infrastructure backing Analytic Feeds. You'll work with us both to extend this product to new use cases like Automated Change Detection, as well as to build new web applications for training and developing new algorithms for products like Custom Model Packages.

The ideal candidate is a backend-focussed engineer who wants to collaborate to develop robust software solutions for surfacing quantitative and qualitative changes in our imagery of the world. You're eager to build intuitive APIs and the data infrastructure that backs them.

Our tech stack is based on a combination of Python and Go web services, deployed to Kubernetes clusters, backed by Postgres, all running on Google Cloud Platform. We extensively leverage open source geospatial and machine learning libraries. 

Impact You’ll Own:

  • Design, develop and maintain geospatial web applications and data pipelines to train and release machine learning models for extracting information from Planet's global imagery.
  • Be responsible for development and operations of customer-facing APIs
  • Work closely with engineers, designers and product managers across cross-functional teams to build a cohesive software platform that solves new customer use cases.
  • Utilize hosted cloud infrastructure such as PubSub, Dataflow and Machine Learning APIs

What You Bring:

  • 5+ years experience developing, shipping and maintaining production software
  • Proficiency building web APIs in Python, deployed to Linux environments
  • Understand tradeoffs between RESTful synchronous and asynchronous HTTPS APIs
  • Experience using, scaling and understanding SQL databases (Postgres or MySQL)
  • Experience working collaboratively as part of a team that uses version control, code reviews, automated testing and regular deployments to manage large shared codebases.

What Makes You Stand Out:

  • You've built software on top of geospatial raster and/or vector datasets and know the open source software stack (e.g. PostGIS, GDAL, rasterio)
  • You've worked with or on teams training and deploying machine learning models, and know the domain language (e.g. precision/recall, overfitting, etc.)

Benefits While Working at Planet:

  • Comprehensive Health Plan
  • Wellness program and onsite massages in specific offices
  • Flexible Time Off
  • Recognition Programs
  • Commuter Benefits
  • Learning and Tuition Reimbursement
  • Parental Leave
  • Offsites and Happy Hours
  • Volunteering Benefits

Some Press About Us: 

Our CEO, Will Marshall featured on TED and featured in a Planet Blog

“Planet: Bringing Space Back Down to Earth”

Tiny, privately owned satellites are changing how we view the Earth features in NBC News

“Planet And Rocket Lab Create Mission Patch To Honor Women In Aerospace” —Planet Blog

Why we care so much about Belonging. 

We’re dedicated to helping the whole Planet, and to do that we must strive to represent all of it within each of our offices and on all of our teams. That’s why Planet is guided by an ultimate  north star of Belonging, dreaming big as we approach our ongoing work with diversity, equity and inclusion.  If this job intrigues you, but you’re thinking you might not have all the qualifications, please... do apply!  At Planet, we are looking for well-rounded people from around the world who can contribute to more ways than just what is listed in this job description.  We don’t just fill positions, we aspire to fulfill people’s careers, most excited about folks who are motivated by our underlying humanitarian efforts.  We are a few orbits around the sun before we get to where we want to be, so we hope you’re excited to come along for the ride. 

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Disclaimer: Local Candidates Only
This company does NOT accept candidates from outside recruiting firms. Agency contacts are not welcome.