AI/ML Engineer

• Work with our modeling and simulation team to conduct a wide variety of analyses in support of government satellite programs in Earth orbits.
• Develop new Machine Learning (ML) algorithms for applications such as:
• Using optical and radar space-surveillance sensors to recognize different types of satellites.
• Scheduling space surveillance sensor networks to find, recognize and track maneuvering satellites.
• Deciding what activities satellites should undertake.
• Conduct Exploratory Data Analysis (EDA) to identify patterns.
• Design, develop, and evaluate machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
• Build, train, and tune predictive models.
• Collaborate with cross-functional teams to identify and solve problems.
• Implement and optimize algorithms for tasks such as anomaly detection, prediction, classification, optimization, clustering.
• Develop High Performance Computing pipelines for scalability and monitoring.
• Work with satellite designers and operations planners.
• Work with experts in astrodynamics, sensors, AI/ML, High Performance Computing (HPC).
• Use programming languages such as Python, C++, or others to leverage existing analysis tools and develop new ones.
• Conduct independent trade studies and technical assessments.
• Review and validate algorithms and results provided by external teams.
• Develop and optionally present actionable technical briefings.

Waypoint’s client is seeking an AI/ML Engineer to support advanced modeling and simulation efforts for government satellite programs. This role will develop and evaluate machine learning algorithms for space-surveillance and satellite applications, working with optical and radar sensor data, predictive models, and high-performance computing environments. The ideal candidate will have experience with Python and/or C++, machine learning techniques, and data analysis, with the ability to conduct independent technical assessments and collaborate with experts in AI/ML, astrodynamics, sensing, and HPC., * Education degree: Computer Science, Data Science, Applied Math, or a related technical field.

• Clearance: TS/SCI, should have current or be able to pass CI polygraph test.
• Experience conducting Exploratory Data Analysis (EDA) to identify patterns.
• Experience designing, developing, and evaluating machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
• Experience building, training, and tuning predictive models.
• Experience implementing and optimizing algorithms for tasks such as anomaly detection, prediction, classification, optimization, clustering.
• Experience developing High-Performance Computing pipelines for scalability and monitoring.
• Experience with programming languages such as Python, C++, or others.
• Ability to conduct independent trade studies and technical assessments.
• Ability to review and validate algorithms and results provided by external teams.

• Flexible schedule: On-site core collaboration hours from 10 am to 3 pm.
• Fully-funded
• Mentoring by experts in AI/ML, HPC, astrodynamics, sensing and other fields.
• Senior staff will have opportunities to serve as principals and team leaders.