Applied Audio ML Engineer

Position Overview

David AI is the first audio data research company that brings 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 by leveraging audio as the gateway. Founded in 2024 by a team of former Scale AI engineers, we quickly established strong collaborations with top FAANG companies and AI labs, also raising a $25M Series A from top-tier investors.

Our Machine Learning team stands at the intersection of cutting-edge research and production systems, transforming raw audio into high-signal data for leading AI labs and enterprises. In the role of Applied ML Engineer, you will play a critical part in building advanced speech and audio models, production inference systems, and robust pipelines that demonstrate the true potential of high-quality data.

Key Responsibilities

• Research, design, and implement solutions using advanced signal processing algorithms and bleeding edge ML models applied to speech and audio.
• Develop production-grade inference algorithms, pipelines, and APIs with cross-functional teams to unlock key insights from our data.
• Collaborate with the Operations team to gather training and evaluation datasets that improve model quality.
• Architect systems that enable resilient and durable inference and evaluation processes.

Required Qualifications

• 5+ years of professional audio ML experience, including DSP and ML audio algorithm development.
• End-to-end ownership of ML pipelines, from proof-of-concept to production deployment.
• Strong coding skills in Python with proficiency in deep learning frameworks such as PyTorch.
• Ability to translate research papers and innovative ideas into high-quality, production-ready code.
• Experience deploying ML systems for production inference using cloud technologies.
• Proven track record in setting ML roadmaps, influencing technical direction, and prioritizing research and infrastructure investments.
• Capability to assess model quality in terms of user experience and business value.

Preferred Qualifications

• PhD or Masters in Computer Science or a related field.
• Experience in training generative AI models.
• Expertise in both classical and machine learning techniques in audio signal processing.

Benefits & Perks

• Rapid career growth at one of the fastest growing Series A companies in a booming industry.
• Competitive salary and equity package.
• Flexible PTO policy.
• Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans.
• Paid lunch and dinner in the office, every day through DoorDash.
• 401k access.