Senior Machine Learning Engineer

Planet; Arlington (VA); Hybrid; USD 161,000 - 201,000; Full time

Benefits offered by this job

Health benefits

Equity

Tuition Reimbursement

Home Office Reimbursement

Commuter Benefits

Job summary

Planet seeks a Senior Machine Learning Engineer to lead embeddings-based change detection and CV techniques on satellite data. You’ll work with data scientists and software engineers to push geospatial analytics to continental scales in a hybrid Arlington, VA role.

Ideal candidates have 10+ years in ML, strong Python, PyTorch/TF, and experience deploying models with Docker/Kubernetes in cloud environments. Security clearance is required.

Qualifications

• 10+ years of relevant experience, 6+ years in ML.
• Experience deploying models at scale.
• Strong geospatial and time-series analytics background.

Responsibilities

• Lead ML model development for defense/intelligence.
• Optimize inference at continental/global scales.
• Advance geospatial analytics and CV techniques.
• Collaborate with product and data science teams.
• Integrate ML pipelines with software platforms.

Skills

Machine Learning

Python

PyTorch/TF

Docker/Kubernetes

Geospatial

Time Series

Computer Vision

Data Wrangling

Big Data

Cloud (AWS/GCP)

Education

Graduate degree in STEM

Tools

Docker

Kubernetes

GeoTIFF

GeoJSON

AWS/GCP tooling

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, Austria, Slovenia, and The Netherlands.

About The Role

Planet’s Analytics Team for Global Monitoring focuses on novel geospatial and time series analytics for customers requiring robust change detection, object detection, and generative AI capabilities. As a Senior Machine Learning Engineer, you will drive hands‑on engineering and modeling for Defense and Intelligence applications. You’ll implement novel embeddings‑based change detection and advanced computer vision techniques. In this role, you will ensure best‑in‑class testing and deploy solutions to run at continental and global scales. You’ll collaborate closely with data scientists and software engineers to drive innovation in remote sensing and large‑scale geospatial analytics. Ideal candidates bring a creative mindset and passion for solving complex geospatial challenges.

This is a full‑time, hybrid role which will require you to work from our Arlington, VA office 3 days per week.

Impact You'll Own

• Spearhead the development of novel algorithms and machine learning models tailored for Defense and Intelligence applications.
• Optimize model performance to execute high-throughput inference at continental and global scales.
• Innovate computer vision, time series, and embeddings‑based techniques to uncover new insights from satellite data.
• Collaborate with product managers, data scientists, and engineers to define requirements and iterate on algorithm designs.
• Integrate ML pre‑processing and inference pipelines seamlessly with adjacent software engineering platforms.
• Establish best‑in‑class testing, validation, and monitoring frameworks for continuous model reliability.

What You Bring

• 10+ years of relevant experience of which 6+ years of experience is in machine learning.
• Ability to conduct a rigorous evaluation of results and internal communication of algorithm failure modes.
• Expertise with data science, time series methods, computer vision, and embeddings.
• Ability to implement, train, and optimize neural networks.
• Experience wrangling large datasets, ideally with geospatial libraries, combined with frameworks like PyTorch/TF for model development and training.
• Ability to experiment with model architectures, and derive data‑driven insights to iteratively improve performance and accuracy.
• Experience writing clean, modular Python code and applying software development best practices (Git, testing, CI/CD).
• Experience deploying models (via Docker, Kubernetes, or similar) with an understanding of best practices for monitoring and maintaining them at scale.
• AWS or GCP experience
• Excellent communication skills, capable of explaining technical topics to diverse audiences.
• Graduate degree in a STEM or analytics‑focused field or equivalent work experience.
• Located in the Washington, DC metro or ability to work and commute to Arlington, VA 3x/week
• Ability to obtain and maintain US Security Clearance

What Makes You Stand Out

• Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
• 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
• Familiarity with techniques like model compression, GPU optimizations, or distributed training pipelines

Application Deadline

November 20, 2026 at 11:59p PT

EAR/ITAR Requirements

This position requires access to export‑controlled information, and as such, employment (or hiring of a contractor) is contingent upon the candidate’s ability to access all applicable export‑controlled information without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.

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
• 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.

US National Salary Range

$160,600 - $200,800 USD

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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 [e-mail] or contact your recruiter with your request. Your message will be confidential and we will be happy to assist you.

Candidate AI Policy

Planet embraces Artificial Intelligence (AI) tools, to prepare for interviews and assessments. They understand that candidates may use various resources, including AI tools, to prepare for interviews and assessments. During any live interview stage or when actively completing assessments for this position, the use of AI tools - e.g. Large Language Models (LLMs), deep fake technology, etc. - is strictly prohibited unless explicitly prompted by an interviewer or assessment instructions. If you are unsure about acceptable use, please contact your recruiter for clarification. If an AI tool or similar technology is desired as an accommodation, please contact [e-mail] with your request for assistance. Your message will be confidential, and we will be happy to assist you. Violation of this policy may result in disqualification of your application.