MLAI Founding Engineer

The company is building the intelligence layer for pilot training by combining cockpit audio avionics telemetry and AI-powered analysis to automate flight debriefs and improve pilot performance.

Already deployed across leading aviation institutions and the U.S. Air Force the platform transforms fragmented flight data into actionable training insights through advanced speech processing multimodal AI and domain-specific reasoning systems.

With strong early traction meaningful funding and an imminent Series A raise the company is scaling rapidly and looking for a Founding ML/AI Engineer to own the intelligence layer from end to end.

This is a rare opportunity to join a small high-caliber team and build AI systems in a safety-critical environment where model quality and real-world impact matter.

• Own the entire AI and machine learning stack from data ingestion through production inference
• Build and improve speech-to-text speaker diarization and audio separation systems for cockpit environments
• Develop AI systems that generate automated flight debriefs and performance assessments
• Build multimodal reasoning systems that combine audio telemetry and contextual aviation knowledge
• Design evaluation frameworks and feedback loops to improve model quality over time
• Architect scalable ML infrastructure and production deployment pipelines
• Work directly with founders on technical strategy and product direction
• Establish engineering standards and best practices for the ML organization
• Build systems capable of operating reliably in safety-critical environments
• Help grow the technical team and evolve into a leadership role as the company scales

• 47 years of experience building production ML/AI systems
• Experience shipping end-to-end ML products into production environments
• Experience at an early-stage startup with significant ownership
• Demonstrated architectural leadership and technical decision-making
• Experience owning ML systems from experimentation through deployment
• Founding Engineer or early engineering team experience preferred
• Aviation aerospace defense or related domain experience strongly preferred

• Deep expertise in NLP speech processing audio ML or related domains
• Strong Python engineering skills
• Experience building and deploying LLM-powered applications
• Experience with RAG prompt engineering model evaluation and fine-tuning
• Experience with multimodal AI systems
• Familiarity with cloud infrastructure and ML deployment workflows
• Strong system design and architecture fundamentals
• Heavy user of AI development tools such as Cursor Claude Code and Copilot

• BS/MS in Computer Science Machine Learning Electrical Engineering or related field preferred
• Strong academic background from a top technical program preferred

• High ownership mentality
• Strong communication and collaboration skills
• Comfortable operating with ambiguity
• Ability to work independently with minimal oversight
• Strong product and business judgment
• Excited by fast iteration and rapid execution

• Aviation technology startups
• Defense technology companies
• Aerospace software organizations
• AI infrastructure startups
• Early-stage venture-backed startups
• Founding Engineer backgrounds
• Teams building production NLP speech or multimodal AI systems

• Base Salary: $170000 $220000
• Competitive founding-stage equity
• Significant ownership and influence over technical direction
• Opportunity to lead the ML function as the company scales
• Direct collaboration with founders
• Exposure to aviation and defense industries
• Free flight training and aviation immersion opportunities
• Visa sponsorship available

This is an opportunity to own the entire intelligence layer of an AI-native aviation platform at an extremely early stage.

Youll work on technically challenging problems spanning speech processing multimodal reasoning time-series analysis and LLM-powered workflows while building systems used by real pilots and military organizations.

As one of the earliest engineers youll have outsized influence on product direction technical architecture and team growth while participating in significant equity upside as the company scales from Seed to Series A and beyond.