Original listing text, shown exactly as published by the company.
About You
You are a technically deep software leader who has shipped production AI or autonomy systems in a safety-critical domain. You thrive at the intersection of rigorous engineering and ambitious product vision, and you know how to build and motivate world-class teams working on hard, long-horizon problems.
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. You're equally comfortable reviewing a pull request, debating system architecture, and presenting a roadmap to the executive team. You want your work to matter, and there's nothing more meaningful to you than putting reliable autonomous systems into the sky.
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.
- Represent the AI Core team in cross-functional planning, risk reviews, and stakeholder communications.
- Track and evaluate emerging research and open-source developments relevant to autonomous flight, and translate promising work into product opportunities.
Qualifications
- 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.
- Experience managing the managers, senior engineers and staff-level technical contributors, including performance management and career development.
- Ability to define and communicate architectural decisions across organizational boundaries, including to non-technical stakeholders.
- Proficiency in Pytorch, TensorFlow and C++ (or equivalent systems languages used in real-time embedded environments).
- Strong written and verbal communication skills; ability to document complex technical decisions clearly and concisely.
- Comfort operating in a fast-paced, ambiguous startup environment where priorities and requirements evolve.
Nice to Have
- Background in vehicle dynamics, vehicle control systems, or avionics/Automotive software integration.
- Familiarity with simulation-based validation, hardware-in-the-loop (HIL) testing, or digital twin development.
- Experience with airborne hardware platforms, embedded Linux, or real-time operating systems (RTOS).
- Published research or significant contributions to open-source projects in autonomy, robotics, or machine learning.
- Prior experience at a Series A–C deep tech startup.
- Pilot's license or meaningful hands-on experience with aircraft operations.
