Planet Labs
jobid=A.0.049
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 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:
- 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
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