Research Engineer, Audio Data & Production ML

David AI; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Unlimited PTO

Health, dental, and vision coverage

FSA/HSA access

401k access

Meals 2x daily via DoorDash

Barry’s classes

Job summary

David AI is seeking a Research Engineer to design algorithms and scalable pipelines that turn large-scale audio datasets into high-quality training data. You will work across signal processing, ML models, and production systems to extract actionable insights from thousands of hours of audio.

You will own ML pipelines end-to-end, translate research into production code, deploy inference systems in the cloud, and collaborate with operations to improve dataset quality and model performance.

Qualifications

• 3+ years of professional engineering or applied research in data systems, algorithms, ML, information retrieval, or speech/audio.
• Strong Python skills and production‑quality software
• End‑to‑end ownership of ML pipelines from PoC to production
• Translate research papers and ideas into production‑ready code
• Experience deploying ML systems for production inference in the cloud
• Assess model quality in context of user experience and business value

Responsibilities

• Design algorithms and metrics using advanced signal processing and ML models to derive insights from thousands of hours of audio data.
• Build scalable data processing pipelines for analyzing, filtering, deduplicating, and curating large speech/audio datasets.
• Develop production‑grade inference algorithms, pipelines, and APIs with cross‑functional teams.
• Collaborate with Operations to gather useful training/evaluation datasets to improve model quality.
• Architect systems enabling resilient, durable inference and evaluations.

Skills

Python

Production software

ML pipelines

Cloud deployment

Translate research

Data systems/algorithms

End-to-end ownership

Model evaluation

Education

Master's or PhD in CS or related

Job description

David AI is seeking a Research Engineer to design algorithms and scalable pipelines that turn large-scale audio datasets into high-quality training data. You will work across signal processing, ML models, and production systems to extract actionable insights from thousands of hours of audio.

You will own ML pipelines end-to-end, translate research into production code, deploy inference systems in the cloud, and collaborate with operations to improve dataset quality and model performance.