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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML/AI Founding Engineer - **Company:** AI Talent Hunt LLC - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $170,000.0 - $220,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cursor (Graphical User Interface Elements), Python (Programming Language), Machine Learning, Azure Machine Learning, Speech Recognition, Data Ingestion, Pytorch, Large Language Models, Prompt Engineering, IT Architecture, Kubernetes, Information Technology, Machine Learning Operations, Data Pipelines - **Published:** July 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6a5323113899d1b7 ## About the Role * 4-7 years of experience building and shipping production ML systems. * Proven experience developing end-to-end machine learning applications. * Experience working in an early-stage startup environment with significant ownership. * Strong architectural and technical leadership capabilities. * Experience within aviation, aerospace, defense, or closely related industries. * Previous experience as a founding or early ML engineer is highly preferred. Education * Bachelor's or Master's degree in Computer Science, Machine Learning, Electrical Engineering, or a related technical discipline. * Degree from a highly regarded computer science program is preferred. Required Technical Skills * Strong expertise in NLP, Speech Processing, Audio Machine Learning, or Multimodal AI. * Advanced Python and PyTorch development experience. * Hands-on experience with Large Language Models, RAG, prompt engineering, and model fine-tuning. * Experience with Speech-to-Text systems and Speaker Diarization. * Knowledge of Audio ML and Time-Series Analysis. * Experience building production MLOps pipelines. * AWS and Kubernetes experience. * Comfortable using AI-assisted development tools such as Cursor and Claude Code. Preferred Qualifications * Experience processing aviation radio or cockpit audio. * Experience with telemetry-based machine learning systems. * Private pilot license or strong personal interest in aviation. * Ability to start immediately or within a short notice period., The ideal candidate is someone who has shipped real production AI systems rather than focusing solely on research. They enjoy building products from the ground up, embrace AI-assisted development workflows, and are excited by the opportunity to own an entire ML platform while helping scale an early-stage company. ## Description AI Talent Hunt is hiring on behalf of its partner for a Founding ML/AI Engineer to build and own the intelligence layer of an AI-powered pilot training platform. This is a unique opportunity to become the first dedicated ML/AI engineering hire, taking full ownership of production machine learning systems from data ingestion through deployment. The ideal candidate has 4-7 years of hands-on production ML experience, thrives in fast-paced startup environments, and is excited to help shape the technical direction of a rapidly growing company. The platform processes complex multimodal data, including cockpit audio, avionics telemetry, and air traffic control communications, to generate automated flight debriefs in a safety-critical aviation environment. This role is based on-site in San Francisco, California, five days per week. Key Responsibilities * Build and optimize production-grade audio intelligence pipelines. * Develop speaker diarization, speech-to-text, and cockpit audio separation systems capable of handling overlapping conversations between pilots, instructors, and air traffic controllers. * Design machine learning systems for automated flight debriefs, including maneuver detection, performance scoring, and safety event classification. * Architect the AI reasoning layer by combining avionics telemetry, cockpit audio, and aviation knowledge into accurate debrief summaries. * Build evaluation frameworks and continuous feedback loops to improve model performance against real-world instructor assessments. * Own the complete ML lifecycle, including data pipelines, model training, deployment, monitoring, and production inference. * Help define the long-term AI architecture while serving as the founding ML engineering leader. ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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