Machine Learning Engineer, Forest Ecosystems

United States, Remote

Planet Labs Inc.

Discover how Planet's daily satellite imagery and insights empower global decisions and actions with a multidimensional view of our changing planet.

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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 world wide 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
#LI-REMOTE

Application Deadline:

June 10, 2025 by 11:59pm PDT

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

  • Comprehensive Medical, Dental, and Vision plans
  • Health Savings Account (HSA) with a company contribution
  • Generous Paid Time Off in addition to holidays and company-wide days off 
  • 16 Weeks of Paid Parental Leave
  • Remote-friendly work environment 
  • Wellness Program and Employee Assistance Program (EAP)
  • Home Office Reimbursement
  • Monthly Phone and Internet Reimbursement
  • Tuition Reimbursement and access to LinkedIn Learning
  • Equity
  • Commuter Benefits (if local to an office)
  • Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below.  Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location.  The range displays our typical hiring range for new hire salaries in US locations only.  Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

New York City + California Salary Range$136,000—$170,000 USDSan Francisco Salary Range$144,500—$180,600 USDUS National Salary Range$127,000—$158,700 USD

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.

Privacy Policy: By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the Planet Data Privacy Notice for California Staff Members and Applicants, and hereby consent to the collection, processing, use, and storage of my personal information as described therein.

Privacy Policy (European Applicants): By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the Candidate Privacy Notice GDPR Planet Labs Europe, and hereby consent to the collection, processing, use, and storage of my personal information as described therein.

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Tags: APIs Architecture CI/CD Classification Computer Science Computer Vision Data pipelines Deep Learning DevOps Docker Engineering Kubernetes Lidar Machine Learning ML models MLOps Pipelines Privacy Python PyTorch Research TensorFlow Testing

Perks/benefits: Career development Equity / stock options Flex vacation Health care Medical leave Parental leave Salary bonus Startup environment Wellness

Regions: Remote/Anywhere North America
Country: United States

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