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Machine Learning Nasa Jobs in Silver Spring, MD (NOW HIRING)

Virtualitics, Inc

Data Scientist

Washington, DC · On-site +1

Founded on a decade of Caltech research in partnership with NASA/JPL, we are led by scientists ... machine learning model in a production environment. * 1-2 years of experience with SQL/NoSQL or ...

Tetra Tech

Senior Data Scientist

Washington, DC · On-site

$155K - $170K/yr

Use advanced statistics, modeling, and machine learning to predict outcomes and solve complex ... NASA or at least the federal government * Must have a Master's Degree in technical area (e.g.

AIToolboard

Data Scientist

Washington, DC · On-site

$150 - $190/hr

Founded on a decade of Caltech research in partnership with NASA/JPL, we are led by scientists ... machine learning model in a production environment • 1-2 years of experience with SQL/NoSQL or ...

New

Tetra Tech, Inc.

Senior Data Scientist

Washington, DC · On-site

$155K - $170K/yr

Use advanced statistics, modeling, and machine learning to predict outcomes and solve complex ... NASA or at least the federal government * Must have a Master's Degree in technical area (e.g.

Galois, Inc.

Principal Scientist

Arlington, VA

With clients including NASA, DARPA, AWS, and the DoW, we leverage our cutting-edge research to ... Artificial Intelligence, Machine Learning, and Data Science * Software & Systems Analysis

Esri

Federal Account Manager - Public Sector

Vienna, VA · On-site

$104K - $187K/yr

You'll be part of a high performing team that helps federal civilian agencies (such as NASA ... Machine Learning (ML), Kubernetes, digital twin, data science, big data, Microsoft Fabric ...

George Mason University

Research Scientist

Fairfax, VA · On-site

Applies machine learning (ML) and artificial intelligence (AI) techniques to enhance traditional ... Contributes to proposal development for external research funding, including NSF, NOAA, NASA, and ...

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Machine Learning Nasa information

What does a machine learning specialist at NASA do?

Machine Learning specialists at NASA use advanced algorithms and data analysis techniques to help solve complex problems in space exploration and research. Their work includes developing models for spacecraft navigation, analyzing satellite imagery, predicting equipment failures, and supporting scientific discoveries through data-driven insights. By leveraging artificial intelligence and machine learning, they help NASA make more accurate predictions, automate processes, and enhance mission safety and efficiency.

What are the key skills and qualifications needed to thrive as a machine learning scientist at NASA?

To thrive as a Machine Learning Scientist at NASA, you need a solid background in computer science, mathematics, and statistics, typically supported by an advanced degree in a related field. Proficiency with programming languages like Python or R, familiarity with machine learning libraries (such as TensorFlow or PyTorch), and experience with large-scale data analysis are essential. Strong problem-solving skills, creativity, and the ability to collaborate across multidisciplinary teams help set top candidates apart. These skills and qualities are crucial for developing innovative AI solutions that support NASA’s scientific missions and research objectives.

What are common challenges faced by machine learning professionals working at NASA, and how can applicants prepare for them?

Machine learning professionals at NASA often work with complex, high-dimensional datasets collected from space missions, satellites, and simulations, which can present unique challenges such as data sparsity, noise, and the need for robust, interpretable models. Collaboration with scientists and engineers from diverse backgrounds is frequent, requiring excellent communication skills to translate technical findings into actionable insights. To prepare, applicants should familiarize themselves with domain-specific data, stay updated on the latest advancements in machine learning, and practice interdisciplinary teamwork to effectively contribute to NASA's innovative projects.
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Machine Learning Nasa jobs near you
Infographic showing various Machine Learning Nasa job openings in Silver Spring, MD as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Scientist

Virtualitics, Inc

Washington, DC • On-site, Remote

Full-time

Re-posted 22 days ago

Job description

Virtualitics is the category leader in AI-native readiness applications for defense, government, and critical infrastructure. Founded on a decade of Caltech research in partnership with NASA/JPL, we are led by scientists, strategists, and servicemembers united by a single mission: to solve the world’s most complex, mission-critical challenges with AI. 

Our Readiness AI solutions deliver operational certainty — giving leaders and operators a clear picture of what’s ready, what’s at risk, and what to do next. By identifying risks early, diagnosing root causes, and recommending prioritized actions with transparent, explainable AI, we help organizations move from data complexity to decision advantage. 

Behind that impact is relentless innovation. Inventors at heart, we hold 15+ U.S. patents and are leading the shift toward agent-driven readiness. But what truly sets us apart is our culture — relentless about results, grounded in transparency, and driven by compassion for the mission and the people it serves.

If you’re motivated by impact, inspired by technical depth, and ready to build AI that performs where it matters most — you’ll find your mission here.

 
Data Scientist TS/SCI (DC/NoVA)
 
Virtualitics introduced Intelligent Exploration to the analytics community through the Virtualitics AI Platform. We are seeking a Data Scientist with TS/SCI security clearance with a strong sense of ownership to join our Platform team. This position has career growth opportunities for those seeking to become Lead Data Scientist and/or Team Manager.
 
As a Data Scientist, you will:
  • Use the capabilities of the Virtualitics AI Platform to deploy production solutions for our customers.
  • Work with customer data and own the development of an AI solution from ideation to production
  • Leverage integrations with big data frameworks (e.g. Databricks) as needed to develop solutions for customers.
Requirements:
  • Must have an active TS/SCI security clearance and be willing to work from a SCIF as needed.
  • Must be located in or near Washington DC/Northern Virginia to be able to access relevant SCIFs.
  • Regular travel anticipated to client sites/military bases.
  • Degree in Computer Science.
  • 3+ years of experience writing production ready code in Python.
  • 3+ years of experience with Python Data Stack: pandas, numpy, sklearn, tensorflow, pytorch, matplotlib, etc.
  • 1 year of experience deploying a machine learning model in a production environment.
  • 1-2 years of experience with SQL/NoSQL or other database systems (elasticsearch, graph databases, etc.).
  • 3 years of experience with Git (or an alternative version control tool).
  • 1 year of Experience with Docker and/or Kubernetes.
  • A strong sense of ownership and accountability.
  • Excellent written and verbal communication skills in English
 
Pluses:
  • Demonstrated experience in leading the development efforts for a project from a SCIF.
  • Experience with PCAP and network monitoring, CVEs and Cyber Vulnerabilities, etc.
  • 1 year of experience integrating applications with at least one of Spark, Dask, Snowpark or Kafka.
  • 1 year of experience with technologies like task schedulers (e.g. Celery, Airflow, Prefect, etc.) and web-app development stacks (e.g.
    Flask/Django)
Compensation and Benefits:
  • Competitive salary/equity/bonus based on experience and education.
  • Full benefits including medical, dental, vision.
  • Unlimited paid time off.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.