Director, AI Core Software

Job description

Job responsibilities

• Define and drive the technical strategy for Merlin's AI Core platform, spanning perception, sensor fusion, decision-making, planning, and control.
• Lead, grow, and mentor a multi-disciplinary team of AI engineers, robotics engineers, and software engineers working on flight-critical autonomy software.
• Collaborate with the VP of Engineering and CTO to translate company-level objectives into clear, achievable technical roadmaps with well-defined milestones.
• Own the architecture of the AI Core stack from data pipelines and model training infrastructure through to real-time onboard inference and control.
• Establish and enforce engineering standards, code quality practices, and safety review processes appropriate for an aviation-grade software system.
• Partner closely with Flight Operations, Systems Engineering, and Certification teams to ensure AI Core software meets FAA and regulatory requirements.
• Drive integration between AI Core components and the broader avionics and vehicle management systems.
• Recruit senior engineering talent and build a culture of technical excellence, ownership, and psychological safety.

Job requirements

• You are a technically deep software leader who has shipped production AI or autonomy systems in a safety-critical domain.
• You hold yourself and your team to the highest standards of software quality and safety — not because the process demands it, but because you genuinely care about the integrity of what you build.
• Degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Applied Math, or a related subject.
• 10+ years of software engineering experience, with at least 5 years in Physical AI technical leadership and engineering management roles.
• Proven track record of shipping production grade AI based autonomy in a safety-critical, deterministic and highly regulated environment (aerospace, automotive, industrial, medical, or similar).
• Deep expertise in at least one of: real-time perception and sensor fusion, motion planning and control, large-scale next gen AI model training and deployment, or onboard inference systems.
• Strong command of modern software engineering practices including AI model distillation, MLOps, CI/CD, rigorous testing strategies, and design-for-safety principles.
• Experience in deploying end-to-end Data strategy to collect, ingest and curate the data for AI model training, simulation and edge deployment.