AI/ML Systems Engineer Technical Advisor (Mid-level)

Responsibilities

• Evaluate advanced AI/ML concepts, systems, technologies, designs, architectures, interfaces to space and ground systems.
• Assist the Program Office with analysis of alternatives to optimize technical, cost, and schedule performance considerations and improve knowledge of system, technology, and architecture tradeoffs.
• Develop briefings and reports including technical and programmatic assessments presenting analysis, results, conclusions, and recommendations.
• Provide acquisition advisory services during technical and cost evaluations of proposals.
• Design, train, and test machine learning models and algorithms.
• Integrate AI models into existing software systems, ensuring scalability and efficiency.
• Preprocess, clean, and analyze large datasets for model training.
• Fine‑tune models for maximum accuracy and performance.
• Work with cross‑functional teams, including data scientists and stakeholders.
• Stay updated on the latest AI advancements and implement new tools.

Required Qualifications

• Bachelor’s degree in science, technology, engineering, or math (STEM) discipline with at least 2 years of experience applying AI to practical solutions.
• Strong proficiency in Python, Java, or R; experience with TensorFlow, PyTorch, and scikit‑learn; deep learning, natural language processing (NLP), and data modeling expertise.
• Judgement, critical thinking, problem‑solving, and analytical skills.
• Interpersonal and communication skills for written reports, group discussion, and oral presentations.
• Education and experience qualifications: Bachelor’s degree with fourteen (14) years or more experience, Master’s degree with twelve (12) years or more experience, or PhD/JD with nine (9) years or more experience.

Desired Qualifications

• Familiarity with cloud platforms (AWS, Google Cloud Platform, Azure), database technologies (SQL, NoSQL), and version control systems (Git).
• Experience in one or more of the following: systems engineering and integration applied to spacecraft, ground, and launch systems; R&D of artificial intelligence/machine learning agents; AI and/or machine learning technologies applied to space systems; small to medium team leadership; technical project/program management.
• Ability to translate implied customer inputs into explicit project requirements, milestones, and deliverables.

Minimum Clearance Required: TS.SCI_wPoly