Location: New York City or San Francisco, CA
Employment Type: Full-time
Focus: Full-Stack Engineering, Audio AI, Data Infrastructure, AI/ML Tooling
Experience: 6+ years
Our client is building the data infrastructure behind the next generation of audio AI.
The company is creating high-quality datasets with the same level of rigor that leading AI labs bring to model development. Their work sits at the intersection of audio, speech, data infrastructure, machine learning, generative AI, and product engineering.
Their belief is simple: audio is one of the key gateways for bringing AI into the real world. Speech is natural, accessible, and already embedded in how people communicate. As voice and audio models become more capable, high-quality training data is becoming one of the industry’s biggest bottlenecks.
Founded by former Scale AI engineers and operators, our client has already brought on leading FAANG companies and AI labs as customers and raised a $50M Series B from top-tier investors.
The engineering team builds the systems that transform massive amounts of raw audio into high-signal training data for leading AI companies.
The work spans:
Engineers operate with high ownership, move quickly, and work across the stack. The team collaborates directly with researchers and operations teams, ships production software frequently, and builds systems that process terabytes of speech data.
Our client is hiring a Staff Full Stack Engineer to help lead the development of products and infrastructure used to understand, evaluate, and manage the audio datasets powering advanced AI models.
This is a highly hands-on role for a senior technical builder who can lead complex full-stack projects, establish engineering standards, mentor engineers, and work directly with researchers to turn ideas into production systems.
The right candidate combines strong product instincts with deep technical execution. They can move from prototype to polished product quickly without sacrificing quality.
Previous audio or AI/ML experience is not required. Our client cares more about technical horsepower, product judgment, curiosity, and the ability to learn quickly.
Relevant technologies include:
Experience with every tool is not required. Strong engineering fundamentals matter more than exact stack match.
The ideal candidate is a Staff-level full-stack engineer who is still deeply hands-on.
They have strong product instincts, technical range, and the ability to lead complex engineering work from ambiguity to production. They care about polished user experiences, scalable systems, and building products that create real customer value.
This person should be excited to build in a fast-moving AI environment where audio, data infrastructure, research, and product engineering all come together.

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