Applied Machine Learning Engineer

The Aerospace Corporation
Colorado Springs, CO
Job Description
The Aerospace Corporation is seeking a Machine Learning Engineer to join their Data Science and Artificial Intelligence Department (DSAID) in Colorado Springs, CO. The ideal candidate will have experience in reinforcement learning, graph theory, and data science, with a strong proficiency in programming languages and ML frameworks. The position requires 100% onsite work and a security clearance.

Requirements

  • Bachelors degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or related technical field(s)
  • 5 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain
  • Strong proficiency in at least two different programming languages (e.g. Python, R, C/C++), and ML frameworks and familiarity with common libraries used for Data Science and Machine Learning, such as pandas, pytorch or JAX.
  • Experience with on and off-policy reinforcement learning algorithms such as Deep Q Learning, A3C, and PPO.
  • Working knowledge of fundamental graph theory and graph neural networks.
  • Hands on experience with container orchestration tooling (Docker, Kubernetes, etc.)
  • Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, data structures, etc.)
  • Working knowledge of Unix/Linux operating systems
  • Ability to obtain and maintain a security clearance, which is issued by the US government. U.S citizenship is required to obtain a security clearance.

Benefits

  • Comprehensive health care and wellness plans
  • Paid holidays, sick time, and vacation
  • Standard and alternate work schedules, including telework options
  • 401(k) Plan
  • Flexible spending accounts
  • Variable pay program for exceptional contributions
  • Relocation assistance
  • Professional growth and development programs to help advance your career
  • Education assistance programs
  • An inclusive work environment built on teamwork, flexibility, and respect
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