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:

Planet’s Built Environment applied machine learning team delivers advanced geospatial products primarily for external customers, with a focus on advanced analytics such as change detection, object detection, and emerging generative AI capabilities. This role is a blend of hands-on engineering and modeling: you’ll implement novel methods (e.g., deep learning for time series and computer vision), ensure best-in-class testing and validation, and deploy solutions to run at continental and global scales. You’ll collaborate with both data scientists and software engineers to drive innovation in remote sensing and large-scale geospatial analytics.

This is a full-time, remote position based in the United States.

Impact You'll Own:

• End-to-end model development & maintenance: Develop new algorithms or methods, implement and test them rigorously, and integrate them into production pipelines.  Contribute to their ongoing maintenance and iteratively improve them.
• Advancing geospatial analytics: Innovate on computer vision, time series, and other ML techniques to uncover new insights from satellite and aerial data
• Cross-functional collaboration: Partner with product managers, data scientists, and engineers to define requirements, validate model outputs, and refine algorithms in iterative cycles
• Collaborating with adjacent ML and software engineering teams  to ensure seamless integration of ML pre-processing and inference steps, defining best practices for efficient deployment and maintenance of geospatial models

What You Bring:

• 6+ years of relevant experience of which 5+ years of experience is in machine learning
• Deep familiarity with time series methods, computer vision, and embeddings; able to implement, train, and optimize neural networks
• Data handling & preprocessing: Experience wrangling large datasets, ideally with geospatial libraries, combined with frameworks like PyTorch/TF for model development and training
• Analytical mindset: Able to experiment with model architectures, and derive data-driven insights to iteratively improve performance and accuracy
• Proven ML engineering experience: Comfortable writing clean, modular Python code and applying software development best practices (Git, testing, CI/CD)
• Hands-on production expertise: You’ve deployed models (via Docker, Kubernetes, or similar) and understand best practices for monitoring and maintaining them at scale
• AWS or GCP experience
• Excellent communication skills, capable of explaining technical topics to diverse audiences
• Master’s degree in a STEM or analytics-focused field or equivalent work experience

What Makes You Stand Out: 

• Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
• Experience implementing advanced time series approaches, including state-of-the-art deep learning architectures (e.g., Transformers, RNN variants) or novel forecasting methodologies that can perform online inference
• Knowledge of coordinate reference systems, geometry manipulations, and common data formats (GeoTIFF, GeoJSON, etc).
• Hands-on experience building geospatial or sensor-driven data products from scratch
• Performance optimization: Familiarity with techniques like model compression, GPU optimizations, or distributed training pipelines
• Passion for innovation: you bring a creative mindset and a capability for solving complex problems while working within the constraints of our compute environment

Application Deadline:

June 5, 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.

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.