Algorithm Developer

Information Technology
Regular Full-Time
Top Secret/SCI


Program Description

This program supports various projects within the Air Force Research Laboratory (AFRL) Sensors Directorate (AFRL/RY).  AFRL/RY includes within its mission the improvement of Air Force intelligence, surveillance, and reconnaissance (ISR) capabilities, through both sensor device enhancements and novel processing of sensor data.  The Air Force employs  ISR information as a strategic element during peacetime, as a tactical enabler during conflict, and as a life-saver during emergencies and natural disasters. The goal of the Sensing, Learning, Autonomy, and Knowledge Engineering (SLAKE) program is to advance Air Force sensing capabilities by employing diverse sensor processing results at a representational or product level that is abstracted from the direct sensing output yet retains crucial information and corresponding uncertainties. Key research areas under SLAKE include Machine Learning (ML), Artificial Intelligence (AI), autonomous systems development, sensor product representations, sensor resource allocations, system architectures, and other mission support needs for AFRL/RY.

Position Description:

The goal of this effort is to support continued work on the creation and maintenance of algorithm and software development within Python that would allow analysts and researchers to understand adversarial behaviors for the Tracking and Fusion, and the Patterns of Life (PoL) teams, and incorporate the analyses into the Insight and Multi-Domain Analysis Development and Evaluation (MAD-E) architecture.


  • Support the development of Multi-Domain Analysis Development and Evaluation (MAD-E).
  • Write, evaluate, and integrate algorithms into the MAD-E baseline.
  • Develop Tracking and Fusion and Pattern of Life algorithms.
  • Create algorithms and software interfaces within Python
  • Create/edit/review interfaces for analysts and researchers which, based on SME opinion, will:
  • Identify/manipulate statistically relevant parameters within big datasets (UNCLASS AND CLASSIFIED)
  • Capitalize on kinematics knowledge and development
    • Support Multiple Intelligence (multi-INT) for fusion analysis using UNCLASSIFIED and CLASSIFIED big data analytics
  • Develop algorithms and capabilities for near-real time assessment of data sets to be ingestible by and interoperable with the Insight architecture
  • Develop a capability to verify a dataset of interest was properly assessed and ingested
  • Write and present technical reports on development activities.
  • Write technical documentation supporting code, program capabilities and “how to” guides.
  • Attend meetings and/or demonstrations, alone or with a team.


A candidate must meet the minimum qualifications listed below.

  • US Citizenship.
  • Bachelor’s Degree.
  • 5+ years’ experience with Patterns of Life analysis and/or algorithm development preferred
  • TS/SCI
  • Proficient in Python, UNIX/LINUX, Java, C++; emphasis on Python.
  • Baseline knowledge of kinematics.
  • Experience with sensor data (GEOINT, SIGINT) and big data sets.
  • Experience with technical writing/documentation, able to interpret and create technical documentation.
  • Experience with modular and distributed programming.
  • Familiar with Gitlab, Github, Bitbucket, Jenkins


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