Senior Machine Learning Engineer

NextGenEnergyJobs; Arlington, Northern (VA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

HSA with company contribution

Paid time off

16 weeks parental leave

Wellness program

Home office reimbursement

Phone and internet reimbursement

Tuition reimbursement

Equity

Commuter benefits

Job summary

Planet designs, builds, and operates the largest constellation of imaging satellites in history.

We are seeking a Senior Machine Learning Engineer to drive hands-on engineering and modeling for defense and intelligence applications, including embeddings-based change detection and advanced computer vision techniques.

Qualifications

• 10+ years of relevant experience, including 6+ years in machine learning.
• Experience wrangling large geospatial datasets and using geospatial libraries.
• Strong Python coding, software development practices, and version control (Git).

Responsibilities

• Drive hands-on engineering and modeling for Defense and Intelligence applications.
• Deploy models to run at continental/global scales with robust testing and monitoring.

Skills

Machine learning

Time series

Computer vision

Embeddings

Python

Git

CI/CD

Docker

Kubernetes

Cloud platforms

Education

Graduate degree in STEM/analytics

Tools

PyTorch

TensorFlow

Geospatial libraries

GeoTIFF

GeoJSON

AWS

GCP

Job description

Planet designs, builds, and operates the largest constellation of imaging satellites in history.

Key Responsibilities

• 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.

Requirements

• 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
• 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
• 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.
• 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)