Machine Learning/Automation Research Engineer

Full-time position at Air Force Research Laboratory, Edwards AFB, CA supporting the research and application of efficient, data-driven artificial intelligence systems that advance our predictive and automation capabilities. This includes algorithm development, uncertainty quantification, error stackups, relevant testbeds, data analysis, remote control of test articles, and other advanced concepts. Duties will range from supporting basic research in the areas of uncertainty quantification and algorithm development to applied technology development including coding, testing, and analysis for in-house research and flight demonstration support.  This is a full-time position with benefits that you can enroll in which includes -  Health, Dental, Vision, Short and Long Term Disability, 401k, 11 Paid Holidays, PTO, and Paid Sick Leave.  The salary range for this position is $70K to $126K.

Qualifications:

• MS or equivalent experience in computer science, machine learning, aerospace engineering, mathematics, or data science
• Expertise with controls algorithms, optimization algorithms, reinforcement learning, state estimation, deep learning, supervised learning, or unsupervised learning
• Experience working in or leading teams of scientists, engineers, and technicians
• Must be a United States Citizen
• Must be able to obtain a Security Clearance

Preferred Qualifications:

• PhD or equivalent experience in computer science, machine learning, aerospace engineering, mathematics, or related technical field
• Proficiency in one or more programming languages such as Python, C++, MATLAB, R, Java, or similar
• Strong background in mathematics, statistics, or probability
• Experience with machine learning frameworks and tools
• Familiarity with Raspberry Pi or FPGAs
• Experience in pattern recognition, reinforcement learning, imitation learning, optimization, state estimation, or unsupervised/supervised learning
• Familiarity with handling uncertainty quantification, sparse measurements, or noisy data
• Familiarity with high-performance computing environments and workflows
• Experience with dynamical and chaotic systems
• Familiarity with controls algorithms, remote systems, or optimal controls
• Experience preparing written reports describing the methods, analysis, and results of experiments.
• Must be organized, punctual, self-motivated, a team player, and a strong communicator
• Demonstrated ability to work in a collaborative research environment.
• Highly motivated to develop space exploration technology.
• Strong communication skills, both written and verbal.  Experience presenting papers at conferences or publishing papers in peer-reviewed journals.