Systems Software Engineer (associate, Experienced or Senior)

Boeing Boeing · Aerospace · Berkeley, MO

Boeing is seeking a Systems Software Engineer to support their Software Development team within the Phantom Works Network Centric Operations team. The role focuses on designing, developing, and implementing platform-agnostic software capabilities for network operations in tactical fighter aircraft. Responsibilities include deriving and quantifying data fusion algorithms, analyzing their accuracy and effectiveness, developing prototype algorithms in C++, Python, or MatLab, and collaborating with customers on requirements. Requires experience with data fusion engines, kinematic correlation, Kalman filters, pattern recognition, multi-modal sensor data fusion, sensor calibration, visualization technologies, sensors, datalinks, and weapons interactions.

What you'd actually do

  1. Derive and quantify data fusion algorithms and techniques
  2. Author and maintain technical description documents, requirements and algorithm analysis memos (AAMs) for data fusion algorithms and techniques
  3. Analyze data fusion techniques for accuracy and effectiveness
  4. Develop prototype algorithms (C++, Python, MatLab, etc)
  5. Partner with software architect(s) to inform effective and efficient algorithm implementation and design

Skills

Required

  • Bachelor's Degree
  • 2+ years' experience with data fusion engines, kinematic correlation techniques and Kalman filters
  • Experience with pattern recognition, multi-modal sensor data fusion, sensor calibration and visualization technologies
  • 2+ years' experience with sensors, sensor management and fusion, datalinks, and/or weapons and their interactions

Nice to have

  • Level 2: Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 2+ years of related work experience OR Bachelor’s Degree and 6+ years of directly related work experience OR 10+ years of related, relevant experience
  • Level 3: Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 5+ years of related work experience OR Bachelor’s Degree and 9+ years of directly related work experience OR 13+ years of related, relevant experience
  • Level 4: Bachelor of Science degree from an accredited course of study in engineering, engineering technology (includes manufacturing engineering technology), chemistry, physics, mathematics, data science, or computer science and 9+ years of related work experience OR Bachelor’s Degree and 13+ years of directly related work experience OR 17+ years of related, relevant experience
  • Data Fusion analysis/software development experience
  • Self-starter with a positive attitude, high ethics, strong analytical and creative problem-solving skills and a track record of working successfully under pressure in a time-constrained environment
  • Skill and ability to: collect, organize, synthesize, and analyze data; summarize findings; develop conclusions and recommendations from appropriate data sources
  • Experience with sensor data such as Radar and various infrared sensors
  • Experience developing and implementing probabilistic models to combine sensor data such as Bayesian reasoning, Kalman filtering and evidence theory
  • Experience with advanced probability statistics and applying in real world scenarios

What the JD emphasized

  • 2+ years' experience with data fusion engines, kinematic correlation techniques and Kalman filters
  • Experience with pattern recognition, multi-modal sensor data fusion, sensor calibration and visualization technologies
  • 2+ years' experience with sensors, sensor management and fusion, datalinks, and/or weapons and their interactions
  • Experience developing and implementing probabilistic models to combine sensor data such as Bayesian reasoning, Kalman filtering and evidence theory

Other signals

  • data fusion algorithms
  • pattern recognition
  • multi-modal sensor data fusion
  • probabilistic models
  • Kalman filtering