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"relocation_assistance": null, "top_startup_sources": [ "yc" ], "posted_at": "2025-08-13T17:45:03.422Z", "apply_url": "https://jobs.ashbyhq.com/david-ai/69ab235c-e5fd-4f56-b5e1-13cc69a1a381", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Staff Product Engineer San Francisco, California, United States About David AI David AI is the first audio data research company. We bring an R&D approach to data-developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human-it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in. David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we've brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors. Our team is sharp, humble, ambitious, and tight-knit. We're looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI. 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We're shaping the future of AI by combining emotional intelligence (EQ) and raw intelligence (IQ) to elevate people's potential. Inflection AI created Pi, the world's first emotionally intelligent AI, to help people work through decisions, emotions, and challenges. Pi is a personal AI agent powered by Inflection AI's foundation model, proving that AI can be personal, empathetic, and contextually aware. About the Role We're looking for a Member of Technical Staff (MTS), Research Engineer focused on voice and audio to help advance the spoken intelligence behind Pi. In this role, you'll work at the intersection of research and production-developing, training, and shipping neural models across the full spectrum of voice: speech synthesis, recognition, audio generation, and real-time spoken dialogue. 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Model Performance Auditing: Evaluating AI model performance across standardized qualitative and quantitative metrics, focusing strictly on task completion accuracy, conversational naturalness, and audio comprehension. Technical Metric Evaluation: Assessing the model's basic computer programming literacy, including its understanding of JSON structures, functions, methods, and ability to reason about structured data within a support context. Representative Dataset Generation: Contributing to the development of diverse, high-quality audio datasets that accurately reflect real customer expectations for clarity, efficiency, and natural conversational flow. Required Expertise To successfully fulfill the deliverables of this project, Contractors must possess deep industry knowledge to craft realistic professional scenarios. Core skillset includes: Demonstrable professional expertise in complex customer support, technical troubleshooting, or conversational AI evaluation. 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For decades, the consumer side of those conversations sucked: long queues, robotic menus, repeated explanations, and advice that is often unhelpful. Most people today still cannot simply say what their problem is in natural language when communicating with businesses. AI changes that. For the first time, companies can have natural conversations with customers at massive scale. Every B2C company - from energy providers to telcos to insurers - will use AI agents to talk to their customers. The number of conversations businesses will handle is going to explode in the coming years. At telli, we are solving the challenges that come with that shift. Today, leading B2C companies like Sky are already using telli to deploy thousands of voice agents to provide their customers with a new experience. 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