Machine Learning Engineer

About the Role

At Advanced Space, we're enabling humanity's return to the Moon and building the technologies that will take us to Mars and beyond. We're looking for a Machine Learning Engineer with 5–8 years of experience to develop innovative ML-driven capabilities that support spacecraft missions, autonomy, navigation, mission planning, and advanced engineering solutions.

This is a hands-on technical role focused on translating complex mission and engineering challenges into practical, data-driven solutions. You'll take ownership of technically complex projects from problem formulation and model development through quantitative evaluation, integration, and operational deployment. You'll work with modern machine learning techniques, including statistical learning, probabilistic modeling, optimization, deep learning, and reinforcement learning, to solve real-world aerospace challenges.

We're looking for someone who enjoys tackling ambiguous technical problems, has a strong foundation in machine learning and software engineering, and is excited to collaborate across disciplines to develop capabilities that support real space missions.

About Advanced Space

Advanced Space exists to enable the sustainable exploration, development, and settlement of space through innovative software, mission services, and technology solutions. As the owner and operator of NASA's CAPSTONE™ mission and the Prime Contractor for AFRL's Oracle mission, we're helping shape the future of cislunar exploration while supporting commercial, civil, and national security customers.

Our team combines deep technical expertise with an entrepreneurial mindset. We move quickly, collaborate across disciplines, and empower every engineer to make meaningful contributions. If you're passionate about solving challenging problems and seeing your work fly in space, you'll fit right in.

What You'll Actually Do

• Develop machine learning solutions for complex engineering challenges.
• Translate mission, operations, and engineering needs into well-defined ML and data-driven problems.
• Design and implement ML-enabled capabilities.
• Own technically complex projects from concept to deployment.
• Build reliable and reproducible ML workflows.
• Evaluate model performance and validate results.
• Integrate ML capabilities into aerospace systems.
• Research and apply emerging technologies.
• Communicate technical findings and recommendations.
• Leverage modern AI-assisted engineering tools.

Who Thrives Here

You have a B.S. in Computer Science, Machine Learning, Software Engineering, Aerospace Engineering, or another relevant engineering, physical-science, or quantitative discipline. Equivalent relevant experience may be considered.

You have 5–8 years of professional experience developing and integrating machine learning, optimization, statistical, or data-driven engineering capabilities.

You have demonstrated experience owning technical problems from initial formulation through implementation, quantitative evaluation, documentation, and stakeholder communication.

You are proficient in Python and modern software engineering practices, including version control, code reviews, automated testing, debugging, and performance profiling.

You have experience with at least one modern ML framework, such as PyTorch, JAX, TensorFlow, or an equivalent.

You understand common machine learning model families, including neural network architectures.

You have experience developing reproducible, end-to-end ML workflows.

You have working knowledge of at least one aerospace domain.

You are familiar with machine learning applications for physical or engineered systems.

You can effectively communicate complex technical concepts and collaborate with multidisciplinary engineering teams.

You take ownership of your work, approach challenges with curiosity, and are comfortable navigating technical ambiguity.

Bonus Points if You Have Experience With

• An M.S. or Ph.D. in Aerospace Engineering, Computer Science, Artificial Intelligence, Robotics, or a related field.
• Applying model-based or model-free reinforcement learning.
• Developing autonomy architectures.
• Building simulation or digital-twin environments.
• Integrating ML-enabled capabilities into guidance, navigation, and control.
• Applying optimization, probability, statistics, and rigorous experimental design.
• Using probabilistic modeling or Bayesian inference.
• Communicating complex technical concepts across various fields.
• Using agentic AI tools to support engineering workflows.

Success is Measured By

• Delivering validated, reliable ML capabilities.
• Developing and integrating machine learning solutions.
• Building reproducible ML workflows.
• Demonstrating measurable model performance.
• Effectively integrating ML capabilities into broader aerospace systems.
• Communicating technical findings clearly.
• Contributing to the continued growth of Advanced Space's capabilities.

Why Join Advanced Space

Work on real missions that are shaping the future of lunar and deep-space exploration. Develop machine learning and autonomy solutions that support spacecraft operations and next-generation space technologies. Collaborate with experts in various fields. Apply cutting-edge ML techniques to challenging, real-world engineering problems. Be part of a growing company where your technical contributions have a direct impact on mission success.

Compensation & Benefits

Base Salary: $124K -$171K (based on experience, qualifications, and location). Signing bonus, quarterly performance bonuses, company-sponsored medical benefits and 401(k), flexible time off, relocation assistance.

Advanced Space is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive workplace for all employees.