AI/ML Engineer (Multiple)

APEX TK LLC•Chantilly, VA

18d•$130,000 - $200,000

About The Position

APEX TK is seeking a highly motivated and skilled Radar Signals Engineer to support a critical government client on cutting-edge aerospace projects. The role works with modeling and simulation teams on analyses supporting government satellite programs in Earth orbits and develops machine learning algorithms for satellite recognition, sensor-network scheduling, satellite tracking, and determining satellite activities. The work includes exploratory data analysis; designing, developing, evaluating, training, and tuning machine learning models; and implementing algorithms for anomaly detection, prediction, classification, optimization, and clustering. The engineer also develops scalable, monitored high-performance computing pipelines and collaborates with satellite designers, operations planners, and experts in astrodynamics, sensors, AI/ML, and HPC. The position uses programming languages and existing analysis tools to conduct technical studies, validate external results, and communicate recommendations through technical briefings.

Requirements

2–10 years of relevant experience.
Bachelor’s degree in a STEM-related field such as engineering, mathematics, physics, aerospace, or computer science.
Active Top Secret/SCI with CI Poly clearance.
Experience performing space-related engineering analysis, including collecting, organizing, and analyzing data, using one or more of C++, Python, R, SQL, PostgreSQL, Linux, MATLAB, VBA, or STK.
Ability to communicate findings and recommendations to internal and external customers.

Nice To Haves

Master’s degree in a STEM-related field.
Experience with other simulation tools and programming languages.
Experience with phenomenological models, including demonstrated ability to model relevant physical phenomena and validate those models.

Responsibilities

Conduct analyses in support of government satellite programs in Earth orbits in collaboration with modeling and simulation teams.
Develop machine learning algorithms for recognizing satellites using optical and radar space-surveillance sensors, scheduling sensor networks to find, recognize, and track maneuvering satellites, and deciding what activities satellites should undertake.
Conduct exploratory data analysis to identify patterns.
Design, develop, and evaluate supervised, unsupervised, and reinforcement-learning algorithms.
Build, train, and tune predictive models.
Collaborate with cross-functional teams to identify and solve problems.
Implement and optimize algorithms for anomaly detection, prediction, classification, optimization, and clustering.
Develop scalable high-performance computing pipelines and monitoring.
Work with satellite designers, operations planners, and experts in astrodynamics, sensors, AI/ML, and HPC.
Use programming languages such as Python and C++ to leverage existing analysis tools and develop new tools.
Conduct independent trade studies and technical assessments.
Review and validate algorithms and results provided by external teams.
Develop and present actionable technical briefings.