Pay
In line with similar jobs
$161K–$201K against $166K–$240K, the middle half of what similar US postings state.
From 1,383 postings in the last year. Stated ranges, not salaries paid.
Senior Machine Learning Engineer
Arlington, VA
Live, first seen by us 74 days ago- Pay
USD 160,600–200,800/yearAnnual period assumed — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
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:
Read the full posting
Before you apply
- Work authorization
- US citizens only
Ability to obtain and maintain US Security Clearance
What you’ll work on
Full postingPlanet’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.
This is a full-time, hybrid role which will require you to work from our Arlington, VA office 3 days per week.
Develop novel algorithms and ML models for Defense and Intelligence applications
Optimize models for high-throughput inference at continental and global scales
Innovate computer vision, time series, and embeddings techniques on satellite data
Build ML pre-processing and inference pipelines that integrate with software platforms
Establish testing, validation, and monitoring frameworks for model reliability
From the employer’s posting
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.
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.
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’ll bring
All qualificationsCore experience
- 10+ years of relevant experience of which 6+ years of experience is in machine learning.
- Excellent communication skills, capable of explaining technical topics to diverse audiences.
- Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
- 11:45pm PT on the date stated below.
- Ability to conduct a rigorous evaluation of results and internal communication of algorithm failure modes.
- Ability to obtain and maintain US Security Clearance
Qualification wording
10+ years of relevant experience of which 6+ years of experience is in machine learning.
Excellent communication skills, capable of explaining technical topics to diverse audiences.
Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
11:45pm PT on the date stated below. Applications are reviewed on a rolling basis. This posting may be removed earlier than projected if a suitable pool of applications has been received. For this reason, we recommend applying as soon as you are able to.
Ability to conduct a rigorous evaluation of results and internal communication of algorithm failure modes.
Ability to obtain and maintain US Security Clearance
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 29, 202674 days ago
- Recorded sightings
- 85
- Last seen by us
- Nov 11, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 74
Similar jobs usually come down between day 8 and day 75.
At Planet, jobs usually come down by about day 41.
From 5,196 similar postings that came down, and 9 of Planet’s. Coming down is not always a hire.
Planet is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Docker
- GCP
- Kubernetes
- PyTorch
Where the posting names them
- 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.
- 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.
- 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
- 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.
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About Planet
- People
- About 1,000 in 2026, up 3% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as PL.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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:
11:45pm PT on the date stated below. Applications are reviewed on a rolling basis. This posting may be removed earlier than projected if a suitable pool of applications has been received. For this reason, we recommend applying as soon as you are able to.
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 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.
AI in Our Interviewing Process: Planet is committed to providing an exceptional interview experience for all candidates. We currently use Metaview to better focus on candidates and less on trying to capture notes. As such, with the candidate's consent, select interviews may be recorded and include a "Planet AI Notetaker" for transcription and summarization purposes. Should an interview involve use of AI interview technologies, the candidate will receive notification and have the ability to opt out both in advance and/or real-time. Opting out will not affect one's candidacy.
Candidate AI Policy: Planet embraces Artificial Intelligence (AI) tools, and we encourage its responsible use. We understand that candidates may use various resources, including AI tools, to prepare for interviews and assessments. However, 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 accommodations@planet.com 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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.
- Location & working pattern
Arlington, VA
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:
More source context
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).
- Work authorization
- 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: