Machine Learning Engineer, Remote Sensing at Planet

Posted on:
February 23, 2023

🔭 Our mission & vision

Job Description

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, and The Netherlands.

About the Role:  

Our team is part of the Planetary Variables organization. We build the ML algorithms that transform Planet’s imagery firehose into semantic data layers, such as cloud masks, land cover maps and change detection, usually deployed at a continental or global scale. Our team’s core competence is the development of probabilistic inference algorithms that transform deep imagery time series into distilled maps of variables. These algorithms are typically a combination of computer vision (DL & non-DL) and time series, all cemented in statistical and physical principles. 

In this role, you will join a team of engineers working together on algorithm development and integration into our distributed compute platform. You will perform exploratory analysis on remote sensing data and build models and inference pipelines on top of our infrastructure. You will also design ML operations to maintain the performance of deployed models and pipelines. Ideally, you have a strong background in applied statistics, a scientific mindset to conduct effective experiments, and solid experience with software engineering principles.

Our team is remote and distributed across North America, with flexible working hours. We make well-being a priority.   

Impact You’ll Own:

Development of computer vision and time series algorithms

Design of datasets to fit or evaluate algorithms

Implementation of algorithms as scalable production code in Python

ML operations to maintain production algorithms (monitoring, training, benchmarking, deploying, etc)

What You Bring:

Solid understanding of fundamentals in remote sensing, statistics and machine learning

Methodical and scientific thinking. Ability to plan and prioritize in time-constrained projects

Experience with distributed and scientific computing

Experience with geospatial python libraries (e.g. GDAL, rasterio, shapely, etc)

Experience with scientific python libraries (e.g. numpy, scipy, TensorFlow, etc)

Fluency in Python in a Linux environment

Experience with Git and Docker

Excellent technical communication and documentation skills

What Makes You Stand Out:

PhD in remote sensing or related field, or research experience with data

Strong background in time series analysis or deep learning

Experience maintaining ML models in production

Benefits While Working at Planet:

Comprehensive Health Plan

Wellness program and onsite massages in specific offices

Flexible Time Off

Recognition Programs

Commuter Benefits

Learning and Tuition Reimbursement

Parental Leave

Offsites and Happy Hours

Volunteering Benefits



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 with diversity, equity and inclusion.  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. 


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 interview process, please call Planet's front office at 669-214-9404 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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