Senior Autonomy Machine Learning Engineer

Are you passionate about shaping the future of humanity's presence in space? Lunar Outpost, a trailblazer in space robotics, invites you to join our team! Lunar Outpost is dedicated to creating a sustainable presence in space, while also driving positive impacts here on Earth. We are seeking a talented Senior Autonomy Machine Learning Engineer.

As a Senior Autonomy Machine Learning Engineer, you will research, develop, train, evaluate, and deploy machine learning models for Lunar Outpost’s lunar rovers, command-and-control platforms, terrestrial robotic systems, and orbital assets. Working at the intersection of robotics, autonomy, AI, and space exploration, you will develop technologies that enable robotic systems to perceive their environment, interpret operator intent, reason about mission objectives, generate plans, and safely execute complex tasks with reduced operator oversight.

Take the #Next Leap with Lunar Outpost and work on the Pegasus LTV, which will carry NASA astronauts farther than they’ve ever been before on the lunar surface!

• Research, design, train, fine-tune, and evaluate transformer-based machine learning architectures for autonomous robotic and command-and-control applications
• Develop vision-language-action models, vision-language models, and other multimodal models that connect operator intent and sensor observations to robot plans and actions
• Build capabilities for natural-language command interpretation, task decomposition, mission planning, action generation, operator decision support, and autonomous task execution
• Develop human-robot teaming capabilities that enable operators to efficiently supervise and command multiple robotic assets
• Create systems for mission summarization, anomaly detection, situational awareness, course-of-action generation, and operator-reviewable recommendations
• Integrate machine learning models with robotic platforms, simulation environments, command-and-control software, and autonomy frameworks
• Conduct hardware-in-the-loop tests, field tests, and structured demonstrations to validate capabilities under realistic operating conditions
• Participate in design reviews, trade studies, technical risk assessments, test-readiness reviews, and demonstrations

• Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Electrical Engineering, Computer Engineering, Aerospace Engineering, or a related technical field, or equivalent practical experience
• 3 to 5 years of relevant professional, academic, or research experience developing machine learning systems, autonomous systems, or intelligent robotic applications
• Experience developing and evaluating deep learning models using Python and a modern machine learning framework such as PyTorch, JAX, or Tensor Flow
• Experience in at least one of the following areas:
  • Vision-language models or multimodal foundation models
  • Robot learning, imitation learning, or reinforcement learning
  • Natural-language planning, tool use, or agentic systems
  • Autonomous planning, reasoning, or task execution
• Experience preparing datasets, implementing training pipelines, defining evaluation metrics, and analyzing model performance
• Strong software engineering skills, including experience writing maintainable and testable software
• Experience with Linux-based development environments, Git, and collaborative software development workflows
• Ability to translate research concepts into working prototypes and evaluate those prototypes against measurable system objectives
• Ability to communicate complex technical concepts, experimental results, limitations, and risks to multidisciplinary teams
• Comfortable working in a research-oriented, agile, and interdisciplinary environment where…