Planet
Aerospace & DefenseDirect Greenhouse career site

Senior Machine Learning Engineer

Pay
$160,600 – $200,800 per year
Location
Arlington, VA
Job type
Full-time
Level
Senior
Listed
30 days ago

Skills & highlights for this role

  • machine learning
  • geospatial analytics
  • time series analysis

Stated benefits & perks

  • Health
  • Dental
  • Vision
  • Parental leave
  • Tuition

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

Read the original posting

From Planet's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.

How Rolev.ai helps with this application

Rolev.ai is a job search and application tool for US job seekers. For this Senior Machine Learning Engineer role at Planet, it shows how your resume fits, tailors your resume to the posting, and prepares the application for you to review.

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Common questions

What is the salary for the Senior Machine Learning Engineer role at Planet?

The Senior Machine Learning Engineer posting at Planet states compensation of $160,600 – $200,800 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Planet's official career site.

Where is the Senior Machine Learning Engineer job at Planet located?

This Senior Machine Learning Engineer position at Planet is located in Arlington, VA. Always check Planet's application page for specific state eligibility or relocation policies.

What qualifications are required for Senior Machine Learning Engineer at Planet?

For the Senior Machine Learning Engineer role, Planet highlights experience with machine learning, geospatial analytics, time series analysis. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.

How do I apply for the Senior Machine Learning Engineer position at Planet?

This listing links directly to Planet's Greenhouse application page. You can apply directly on Planet's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.