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Remote Machine Learning Jobs in Herndon, VA (NOW HIRING)

Planet

Senior Machine Learning Engineer

Arlington, VA · On-site +1

$120K - $165K/yr

As a Senior Machine Learning Engineer, you will drive hands-on engineering and modeling for Defense ... Practical knowledge of remote sensing, satellite imagery, or related geospatial domains * Knowledge ...

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Remote Machine Learning information

See Herndon, VA salary details

$26.2K

$43.8K

$90.5K

How much do remote machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote machine learning in Herndon, VA is $43,790.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,400.00 and $47,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs

What are the most commonly searched types of Machine Learning jobs in Herndon, VA?

The most popular types of Machine Learning jobs in Herndon, VA are:

What are popular job titles related to Remote Machine Learning jobs in Herndon, VA?

For Remote Machine Learning jobs in Herndon, VA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning jobs in Herndon, VA look for?

The top searched job categories for Remote Machine Learning jobs in Herndon, VA are:

What cities near Herndon, VA are hiring for Remote Machine Learning jobs?

Cities near Herndon, VA with the most Remote Machine Learning job openings:

Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Herndon, VA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $43,790 per year, or $21.1 per hour.

Senior Machine Learning Engineer

Planet

Arlington, VA • On-site, Remote

$120K - $165K/yr

Full-time, Part-time

Medical, Dental, Vision, PTO

Posted 8 days ago

Key responsibilities

  • Drive hands-on engineering and modeling for geospatial analytics, including implementing novel embeddings-based change detection and advanced computer vision techniques.

  • Ensure best-in-class testing, validation, and deployment of models to run at continental and global scales.

  • Collaborate with data scientists and software engineers to define requirements, iterate on algorithm designs, and integrate ML pipelines with software platforms.

Job description

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.

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