AI/ML Engineer (Multiple)

Apex Tk; Chantilly (VA); On-site; USD 90,000 - 130,000; Full time

Job summary

Apex Tk is seeking a Radar Signals Engineer to support government satellite programs in Earth orbits. You will collaborate with modeling, simulation, and sensor teams to develop ML algorithms, perform data analyses, and evaluate predictive models using Python, C++, and MATLAB.

You will work with astrodynamics and HPC experts, conduct trade studies, and present actionable briefings on algorithm performance, anomaly detection, classification, and optimization. A TS/SCI clearance is required.

Qualifications

• 2–10 years of relevant space-related engineering analysis experience.
• Active Top Secret/SCI w/ CI Poly Clearance.
• Experience collecting, organizing, and analyzing data using C++, Python, R, SQL, PostgreSQL, Linux, MATLAB, VBA, or STK.
• Ability to communicate findings and recommendations to internal and external customers.

Responsibilities

• Collaborate with modeling and simulation teams to analyze government satellite programs in Earth orbits.
• Develop ML algorithms for space-surveillance applications such as satellite recognition and tracking.
• Conduct exploratory data analysis, design and evaluate ML models, and build predictive pipelines.
• Work with satellite designers and operations planners, and present technical briefings on results.

Skills

Analytical thinking

Communication

Education

Bachelor's degree in STEM

Master's degree in STEM

Tools

Python

C++

R

SQL

PostgreSQL

Linux

MATLAB

VBA

STK

Job description

APEX TK is seeking a highly motivated and skilled Radar Signals Engineer to join our team supporting a critical government client. This position offers the opportunity to work on cutting-edge projects within the aerospace domain.

Responsibilities:

• 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

• Algorithm development will include steps such as
  • Conducting Exploratory Data Analysis (EDA) to identify patterns
  • Designing, developing, and evaluating machine learning algorithms, including supervised, unsupervised, and reinforcement learning
  • Building, training, and tuning predictive models
  • Collaborating with cross-functional teams to identify and solve problems
  • Implementing and optimizing algorithms for tasks such as anomaly detection, prediction, classification, optimization, clustering
  • Developing 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 present actionable technical briefings

Required Qualifications:

• 2-10 years of relevant experience.
• Bachelor’s Degree in a STEM related field such as Engineering, Mathematics, Physics, Aerospace, Computer Science, etc.
• Active Top Secret/SCI w/ CI Poly Clearance
• Experience performing space-related engineering analysis (collecting, organizing, analyzing data) using one or more of the following: C++, Python, R, SQL, PostgreSQL, Linux, MATLAB, VBA, or STK
• Ability to communicate findings and recommendations to internal and external customers

Preferred Qualifications:

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