Software Engineer

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 seeking a talented Software Engineer with expertise in developing and deploying machine learning solutions at scale to join our team. This role is at the intersection of machine learning (ML), software engineering, and remote sensing, focusing on building innovative systems that extract actionable insights from satellite imagery for applications in agriculture, forestry, climate, land management and more. Our projects include mapping crop activities, detecting land changes, measuring forest carbon stocks, roads, buildings and other topics at the intersection of machine learning, artificial intelligence, and Earth Observation. You'll join a passionate, innovative, and distributed team that values collaboration and fosters a culture of continuous learning and impact-driven engineering.

In this role, you will work with a team to develop and deploy robust, scalable machine learning workflows, including computer vision and time-series algorithms, and integrate them into distributed systems for real-world applications. You will analyze remote sensing data from diverse sources to extract actionable insights. Your work will involve designing and enhancing machine learning infrastructure for training, evaluation, and inference on global-scale datasets, ensuring performance and reliability. Additionally, you will contribute to end-to-end system development, including backend and API design, with occasional involvement in front-end and DevOps tasks to ensure seamless functionality of geospatial applications. Collaboration will be key as you work closely with a distributed team of scientists, engineers, and clients across Europe and North America, incorporating feedback to refine and enhance products. You will also establish and maintain machine learning operations workflows to monitor and optimize the performance of deployed models.

This is a full-time position working on a hybrid basis from our Haarlem office 2-3 days per week.

Impact You’ll Own:

• Develop and deploy ML models: Build and integrate robust, scalable machine learning workflows, including computer vision and time-series algorithms, into distributed systems for real-world applications.
• Scalable infrastructure: Design and improve ML infrastructure for training, evaluation, and inference on global-scale datasets, ensuring high performance and reliability.
• End-to-end system development: Contribute to full-stack development, from backend and APIs to occasional front-end and DevOps tasks, enabling seamless integration and functionality of geospatial applications.
• Collaborative innovation: Work closely with a distributed team of scientists, engineers, and clients across Europe and North America, incorporating feedback to refine products and processes.
• ML Ops: Establish and maintain machine learning operations workflows to monitor and enhance deployed models' performance over time.

What You Bring:

• Bachelor's degree in Software Engineering/Computer Science or related discipline 
• 4+ years of relevant work experience
• 3+ years of experience engineering in Python/Java/Go and/or similar programming languages
• 2+ years of experience developing and designing Computer Vision and/or Machine Learning technologies and systems.
• Experience delivering production-grade machine learning systems at scale, with a focus on real-world applications.
• Experience with MLOps workflows to monitor, maintain, and optimize deployed machine learning models.
• Problem-solving skills and ability to iterate based on feedback from clients or partners.
• Proficiency in machine learning frameworks such as TensorFlow or PyTorch, and distributed computing for large-scale data processing.
• Experience with end-to-end system design, including backend development, database management, and occasional front-end contributions.
• Knowledge of computer vision and time-series modeling techniques, applied to real-world datasets.
• Ability to work effectively in a collaborative, cross-disciplinary, and distributed team environment.
• Ability to communicate in English, the working language of the company

What Makes You Stand Out:

• Familiarity in remote sensing and geospatial data processing, including handling dense temporal satellite imagery.

Benefits While Working at Planet:

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

• 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
• Equity 
• Volunteering Paid Time Off

#LI-REMOTE

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.