Data Scientist, Machine Learning and AI - Advanced Development Programs

Job Locations US-WA-Kent
Advanced Development Programs
Job ID


As part of a small, passionate and accomplished team of experts, you will help build industry-leading technology for launch and space systems. In this role, you will help apply machine learning and artificial intelligence techniques to advance the design, build, and operation of Blue Origin’s launch systems and vehicles. As a Data Scientist, you will work with talented peers in the areas of propulsion; guidance, navigation and control (GN&C); autonomy; avionics; manufacturing; and robotics to develop novel algorithms and modeling techniques for human spaceflight systems to support of our vision of millions of people living and working in space.  This position will directly impact the history of space exploration and will require your dedicated commitment and detailed attention towards safe and repeatable spaceflight.


  • Participate in the design, development, evaluation, deployment and updating of data-driven models, prototypes, and analytical solutions for machine learning (ML) and/or artificial intelligence (AI) for launch and space systems or vehicles.
  • Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering.
  • Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities to apply ML and AI techniques to traditional aerospace areas.
  • Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Routinely build and deploy ML models on available data.
  • Research and implement novel ML and statistical approaches to add value to the business
  • Support the infusion of your ideas and technologies into major development programs
  • Mentor junior engineers and scientists.


  • Minimum of a M.S. degree Electrical or Aerospace Engineering, Computer Science, or Mathematics with a specialization in machine learning or artificial intelligence
  • 5+ years of relevant work experience in machine learning, artificial intelligence, or related area
  • Demonstrated technical expertise and experience with advanced machine learning methods and techniques, probabilistic reasoning, deep learning (DL), computer vision (CV), and/or pattern recognition.
  • Strong statistical knowledge, intuition and experience working with physical systems and models
  • Stellar written and verbal communication skills, an ability to communicate even the most complicated methods and results to a broad, often non-technical audience
  • Demonstrated ability to perform both theoretical (e.g., modeling, simulation, analysis, design) and applied (implementation, testing, and validation) development of advanced algorithms and data processing techniques
  • Applicant must be a United States citizen or permanent resident alien (current Green Card holder)


  • Ph.D. degree Electrical or Aerospace Engineering, Computer Science, or Mathematics with a specialization in machine learning or artificial intelligence
  • Familiarity with applying machine learning techniques to real-time, safety-critical systems
  • Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
  • Solid software development experience with strong object-oriented design and coding skills (C/C++ and/or Python on a UNIX or Linux platform), including translating ML models into production software
  • Facility with machine learning frameworks such as Scikit-Learn, Keras/TensorFlow/Theano, MXNet, Pytorch; familiarity with Amazon Web Services (AWS); and familiarity with analyses and simulation languages such as R, MATLAB, and Simulink
  • Demonstrated strength in both supervised and unsupervised learning
  • Familiarity with software verification and validation for safety-critical systems
  • Ability to obtain and retain a security clearance



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