Overview
Skills
Job Details
Who are we?
We're an early-stage, high-growth startup at the intersection of AI and audio. Our mission is to bring AI into the real world starting with sound. Audio is the most human, accessible, and versatile input and we believe its the gateway to truly intelligent systems. Our team is pioneering a new category by applying rigorous R&D practices to the creation of high-quality audio datasets that fuel next-generation models.
In less than a year, we've secured partnerships with top AI labs and most of FAANG, raised $5M+ from leading investors, and built a team of ambitious, humble, and mission-driven builders. Now were hiring applied ML engineers to help us unlock the full potential of audio AI.
What's in it for you?
• Build generative AI models that directly advance the field of speech and audio
• Full ownership over ML pipelines from research to real-world deployment
• Work with a tight-knit team of former AI infrastructure builders from top companies
• Rapid career growth at one of the fastest-moving companies in a booming space
Benefits:
• Competitive salary + equity
• 100% paid health, dental, and vision insurance
• Daily paid meals via DoorDash
• Flexible PTO + 401k access
• Visa sponsorship available
What will you do?
• Research and develop advanced ML models for speech and audio use cases
• Translate cutting-edge research into high-quality production Python code
• Own the full ML pipeline from POC to deployment in cloud environments (AWS or Google Cloud Platform)
• Build APIs and inference systems that surface insights from high-quality data
• Work cross-functionally with Operations to source, shape, and evaluate training datasets
• Architect resilient infrastructure for model training, evaluation, and production inference
• Help define the company's ML roadmap and lead investments in research and tooling
What will you need?
• 5+ years of experience in machine learning, with at least 2 years in DSP/audio ML
• Demonstrated experience shipping ML systems end-to-end (not just research)
• Strong Python skills and proficiency in deep learning frameworks like PyTorch
• Expertise in cloud environments (AWS or Google Cloud Platform) for training and deploying models
• Ability to think holistically about model performance, UX, and business value
• Experience in speech or audio research and/or production
Bonus points for:
• Experience training generative AI models
• PhD or Masters in Computer Science, ML, or a related field
• Leading ML teams and driving technical direction
• Experience building classical and ML-based audio signal processing systems
• Startup experience, particularly in zero-to-one product development