Machine Learning Engineer, Forest Ecosystems

Planet
Canada
Remote
CAD 80,000 - 120,000
Job description

Machine Learning Engineer, Forest Ecosystems

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 a global company with employees working remotely worldwide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.

About the Role:

We are looking for a talented software engineer to join our Forest Ecosystems team. We are a cross-functional team, with a highly collaborative culture, distributed remotely across the USA and Canada. In this role, you’ll work at the intersection of machine learning (ML), software engineering, and remote sensing to develop, optimize, deploy, and maintain ML models that scale.

You’ll collaborate closely with engineers and data scientists to improve algorithms, integrate models into our distributed computing platform, and optimize and execute data pipelines. You’ll help maintain production ML models, support model performance monitoring, and design new workflows that enhance efficiency and reliability.

The Forest Ecosystems team is on a mission to map, measure, and monitor the world’s forests using high-resolution satellite imagery. We convert satellite imagery into quantifiable metrics like tree height and aboveground carbon using spatially-explicit deep learning models. We are continuously improving our models by expanding and curating our datasets, experimenting with different data sources (including optical, SAR, and LiDAR), and experimenting with cutting-edge model architectures.

This is a full-time position based remotely in the United States or Canada.

Impact You'll Own:

  • Establish and maintain machine learning operations workflows for regular data generation
  • Run experiments to evaluate machine learning algorithms
  • ML operations to maintain production algorithms (monitoring, training, benchmarking, deploying, etc)
  • Develop and implement automated testing to ensure the reliability of deployed models
  • Contribute to full-stack development, from backend and APIs to DevOps tasks and occasional front-end work

What You Bring:

  • Bachelor's or Master's degree in Computer Science or a related field
  • 4+ years of professional experience in software engineering of which 2+ years of this is experience in developing and designing Computer Vision and/or Machine Learning technologies and systems
  • Proficiency with Python and machine learning frameworks like TensorFlow or PyTorch
  • Proficiency with software engineering best practices such as version control, testing and continuous integration/continuous deployment (CI/CD)
  • Experience with containerization and container orchestration tools like Docker, Kubernetes, Flyte or Temporal
  • Experience implementing model versioning, monitoring and observability systems
  • Excellent technical communication and documentation skills

What Makes You Stand Out:

  • Experience in remote sensing and geospatial data, particularly raster and LiDAR data
  • Fluency with geospatial technologies in Python (e.g. GDAL, rasterio, shapely, STAC, xarray, etc)
  • Experience with deep learning at scale in a geospatial and/or remote sensing context
  • Demonstrated experience in managing large MLOps production workflows

Application Deadline:

June 10, 2025 by 11:59pm PDT

Benefits While Working at Planet:

  • Extended Health and Dental Coverage
  • Health Spending Account
  • RRSP with company contribution
  • Paid time off including vacation, holidays and company-wide days off
  • Remote-friendly work environment
  • Employee Wellness Program
  • Home Office Reimbursement
  • Monthly Phone and Internet Reimbursement
  • Tuition Reimbursement and access to LinkedIn Learning
  • Quality of Life Stipend
  • Equity

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. 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.

EEO statement:
Planet is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. Planet is an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. Know Your Rights.

Accommodations:
Planet is an inclusive community and we know that everyone has their own needs. If you have a disability or special need that requires accommodation during the hiring process, please reach out to accommodations@planet.com or contact your recruiter with your request. Your message will be confidential and we will be happy to assist you.

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