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

Halvik

Software Developer

Greenbelt, MD

... Machine Learning, Cyber Security and Cutting-Edge Technology across the US Government. Be a part of something special! Position Overview NASA SEWP is seeking a mid-level Java Software Developer to ...

Halvik

Software Developer

Greenbelt, MD · On-site

$100K - $110K/yr

... Machine Learning, Cyber Security and Cutting-Edge Technology across the US Government. Be a part of something special! Position Overview NASA SEWP is seeking a mid-level Java Software Developer to ...

Halvik

Software Developer

Greenbelt, MD · On-site

$100K - $110K/yr

... Machine Learning, Cyber Security and Cutting-Edge Technology across the US Government. Be a part of ... Core ResponsibilitiesDevelop and implement new web applications to support the NASA SEWP ...

Tetra Tech

Senior Data Scientist

Washington, DC · On-site

... machine learning to predict flight outcomes, and optimizing air traffic management processes ... NASA or at least the federal government • Must have a Master's Degree in technical area (e.g.

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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.

Machine Learning Engineer

Virtualitics, Inc

Washington, DC

Full-time

Re-posted 21 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.

 
Machine Learning Engineer - US TS/SCI Clearance (DC Metropolitan Area)
 
Virtualitics is trailblazing Intelligent Exploration and Enterprise AI with our cutting-edge AI Platform. We are hiring an ML Engineer with the capability and readiness to obtain a U.S.-government security clearance. This role is pivotal in bridging the worlds of machine learning, data engineering, and software development to enhance our AI data applications. Career advancement opportunities are available for those interested
in senior engineering positions and technical leadership.
 

As an ML Applications Engineer, you will:

  • Spearhead platform upgrades, ensuring our products are at the forefront of innovation and effectiveness.

  • Craft and manage dynamic dashboards using the Virtualitics AI Platform Python SDK, transforming data into intuitive visuals for decision-making.

  • Optimize data access patterns, enhancing the efficiency and performance of our AI solutions.

  • Tackle runtime performance issues, ensuring high responsiveness and stability of applications.

  • Architect robust, scalable, and user-friendly applications, considering current trends and future growth.

  • Collaborate closely with Technical Product Managers to drive usability enhancements, ensuring our products meet and exceed user expectations.

Requirements:

  • A degree in Computer Science or related field, or 4+ years of software engineering experience.

  • Must have a TS/SCI security clearance.

  • Must be willing to travel and work from a SCIF as needed.

  • Proven track record of deploying software into production environments.

  • Proficiency in Python with a solid understanding of Python Data Stack (pandas, NumPy, scikit-learn, PyTorch, Matplotlib, etc.).

  • Experience with big data technologies and frameworks (Spark, Databricks, Snowflake, etc).

  • Familiarity with Docker, Kubernetes, and Git.

  • Exceptional problem-solving skills and a keen sense of ownership.

  • Excellent communication skills in English, both written and verbal.

Pluses:

  • Experience in Machine Learning Engineering roles and the end-to-end lifecycle of AI applications, from model development to deployment.

  • Experience with Predictive Maintenance, Supply Chain, Scheduling Optimization, etc.

  • Experience with PCAP and network monitoring, CVEs and Cyber Vulnerabilities, etc. 

  • 1 year of experience with technologies like task schedulers (e.g. Celery, Airflow, Prefect, etc.) and web-app development stacks (e.g. Flask/Django) or app building kits like Streamlit/Plotly Dash.

Compensation and Benefits:

  • Competitive salary/equity/bonus based on experience and education.

  • Comprehensive benefits package including medical, dental, and 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.