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Machine Learning Nasa Jobs in Pennsylvania (NOW HIRING)

TAIT

Data Engineer

Lititz, PA · On-site

$106K - $127K/yr

... Nike, NASA, Bloomberg, Google, Beyoncé, and The Olympics TAIT is looking for a hands-on Data ... Experience enabling machine learning or AI solutions through feature engineering, model-ready ...

Tait

Data Engineer

Lititz, PA · On-site

$106K - $127K/yr

... Nike, NASA, Bloomberg, Google, Beyoncé, and The Olympics TAIT is looking for a hands-on Data ... Experience enabling machine learning or AI solutions through feature engineering, model-ready ...

BWX Technologies, Inc.

Director, Quality

Indiana, PA · On-site

$131 - $207/hr

Department of Energy and NASA facilities. BWXT's technology is driving advances in medical ... Facilitate a learning organization driving down escapes, rework and scrap by generating sound root ...

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Machine Learning Nasa information

See Pennsylvania salary details

$18.9K

$105.3K

$192.1K

How much do machine learning nasa jobs pay per year?

As of Aug 25, 2026, the average yearly pay for machine learning nasa in Pennsylvania is $105,274.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,484.00 and $142,162.00 per year, depending on experience, location, and employer.

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.

Does NASA use machine learning?

NASA employs machine learning techniques across various projects, including satellite data analysis, spacecraft navigation, and climate modeling. Machine learning helps improve data processing efficiency and supports autonomous systems in space exploration. Job roles in this field often require knowledge of data science, programming, and domain-specific applications.

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    Machine Learning Nasa jobs near you

    Robotics Research Intern, Robot Learning (Fall 2026) | PhD Part-time Internship

    Pittsburgh, PA • On-site

    FieldAI
    See more jobs at FieldAIexternal

    $55 - $59/hr

    Full-time, Part-time, Internship

    Re-posted 18 days ago

    Job description

    Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
    We are offering a Summer 2026 internship in Robot Learning for students interested in advancing embodied intelligence through large-scale learning, foundation models, and real-world robotic deployment. As a research intern, you will work closely with FieldAI researchers and engineers to explore novel approaches to robot learning and autonomy, with a focus on scalable methods that generalize across tasks and embodiments.
    This internship is designed for PhD students who want to connect cutting-edge AI research with practical robotics systems. You will have the opportunity to design experiments, develop learning pipelines, and validate ideas on real robotic platforms, contributing directly to FieldAI's deployed autonomy stack.
    What You Have:
    • Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
    • Research experience in robot learning, reinforcement learning, imitation learning, or related areas.
    • Strong foundation in machine learning fundamentals and experimental methodology.
    • Develop multi-modal data collection platform for day/night robot navigation data collection
    • Collect high-quality datasets for reproducible and comparable research and evaluation
    • Summarize and publish learnings in high-quality robot research conference or journal
    • Ability to work independently while collaborating effectively in a research environment.
    • Strong interest in embodied intelligence and real-world robotics systems.
    The Extras That Set You Apart
    • Prior experience working with real robot platforms.
    • Familiarity with ROS or ROS 2.
    • Experience with large-scale or distributed training systems.
    • Publications or open-source contributions in robotics or AI.
    • Background in perception, planning, or control for robotics.
    • Interest in bridging foundational research with deployed robotic systems.

    $55 - $59 an hour
    What You Have:
    • Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
    • Research experience in robot learning, reinforcement learning, imitation learning, or related areas.
    • Strong foundation in machine learning fundamentals and experimental methodology.
    • Develop multi-modal data collection platform for day/night robot navigation data collection
    • Collect high-quality datasets for reproducible and comparable research and evaluation
    • Summarize and publish learnings in high-quality robot research conference or journal
    • Ability to work independently while collaborating effectively in a research environment.
    • Strong interest in embodied intelligence and real-world robotics systems.
    The Extras That Set You Apart
    • Prior experience working with real robot platforms.
    • Familiarity with ROS or ROS 2.
    • Experience with large-scale or distributed training systems.
    • Publications or open-source contributions in robotics or AI.
    • Background in perception, planning, or control for robotics.
    • Interest in bridging foundational research with deployed robotic systems.

    Our salary range is generous and we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience.
    Why Join Field AI?
    We are solving one of the world's most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.
    You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
    Be Part of the Next Robotics Revolution
    To tackle such ambitious challenges, we need a team as unique as our vision - innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We're seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.
    We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates.
    Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
    We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.
    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.

    Apply