AI​/ML Research Scientist

Title: AI/ML Research Scientist

Company: Heven Aero Tech

Location: Sterling, Virginia

FLSA: Exempt

About Our Company: We don’t just believe in the power of people—we build our success on it. As a recognized leader in hydrogen‑powered drones, we’ve earned recognition for creating a workplace where innovation thrives, collaboration is second nature, and every employee feels valued. Our culture is anchored in trust, and a shared commitment to excellence. We know that great organizations are built by extraordinary teams.

That’s why we invest in your professional growth, offering robust training programs, leadership development opportunities, and a clear pathway for advancement.

The AI/ML Research Scientist will lead pioneering research at the intersection of artificial intelligence, quantum technologies, hydrogen systems, and autonomous aerospace operations. This role requires conducting applied research that bridges cutting‑edge academic theory with mission‑critical defense applications, publishing findings, filing patents, and influencing the technical direction of our autonomous systems portfolio while generating foundational intellectual property for next‑generation autonomous UAS.

• Design and implement AI/ML algorithms for autonomous navigation, including visual‑inertial odometry, SLAM, and sensor fusion.
• Architect adversarial robustness frameworks and edge AI optimizations tailored for mission‑critical defense applications.
• Create predictive models for hydrogen fuel cell performance and thermal management.
• Build physics‑informed neural networks and digital twin simulations for aerospace systems.
• Research quantum sensing integration methods for navigation and perception.
• Document research findings and prepare invention disclosures for patent applications.
• Write technical specifications for proprietary algorithms and system architectures.
• Publish research papers and present at conferences.
• Maintain detailed records of experimental results and methodologies.
• Develop proof‑of‑concept software in simulation and hardware‑in‑the‑loop environments.
• Collaborate with engineering teams to integrate research algorithms into UAS platforms.
• Conduct testing and validation of algorithms using real‑world flight data.
• Troubleshoot and refine models based on experimental performance.
• Participate in technical design reviews and provide AI/ML expertise.
• Coordinate with university partners and industry collaborators on joint research.
• Support proposal development for research funding opportunities.
• Track emerging AI/ML technologies relevant to autonomous aerospace systems.

Required:

• Ph.D. in Computer Science, Electrical Engineering, Aerospace Engineering, Applied Mathematics, Physics, or related field with dissertation in machine learning, robotics, autonomous systems, computer vision, or control theory.
• 3+ years post‑Ph.D. research experience in AI/ML.
• Minimum 3 peer‑reviewed publications with at least one first‑author paper.
• Expert knowledge of deep learning architectures (CNNs, transformers, reinforcement learning) and probabilistic machine learning.
• Proficiency in PyTorch, Tensor Flow, or JAX; strong Python skills.
• Experience with computer vision, sensor fusion, or state estimation.
• Ability to obtain DoD Secret clearance within first year.

Preferred:

• 5+ years post‑Ph.D. research experience with 10+ publications and H‑index ≥ 3.
• Patent applications or issued patents in AI/ML or autonomous systems.
• Domain expertise in one or more of: robotics/ROS, aerospace/flight dynamics, quantum computing, physics‑informed ML, edge AI optimization, or adversarial ML.
• Proven record of transitioning research into practical applications, complemented by grant writing and Principal Investigator (PI) experience.

• The ability to maintain a stable, upright seated or standing position for extended periods (typically 6–10 hours per day) without significant physical fatigue.
• High‑frequency use of fingers and wrists for data entry, complex coding, and navigating digital interfaces using keyboards and mice.
• The capacity for “near‑point” visual tasking, involving the ability to focus on…