5+ years of professional audio ML experience, focusing on DSP and algorithm development.
Proven end-to-end ownership of ML pipelines from concept to production.
Strong coding skills in Python with proficiency in PyTorch and other deep learning frameworks.
Ability to convert research ideas into high-quality code for production use.
Experience in deploying ML systems in cloud environments for production inference.
Demonstrated track record of influencing ML technical direction and roadmaps.
Capability to evaluate model quality concerning user experience and business value.
Responsibilities
Research, design, and implement advanced signal processing algorithms and ML models for speech and audio applications.
Develop production-grade inference algorithms, pipelines, and APIs in collaboration with cross-functional teams.
Collect training and evaluation datasets by working closely with the Operations team to enhance model quality.
Architect robust systems for resilient inference and model evaluations.
Showcase the potential of high-quality data through system developments and enhancements.
Benefits
Opportunities for rapid career advancement in a growing Series A company.
Flexible paid time off (PTO) policy.
Comprehensive health, dental, and vision insurance with full reimbursement for most plans.
Daily office meals provided through DoorDash for lunch and dinner.
Access to a 401k retirement plan.
Full Job Description
About our Machine Learning team
Our Machine Learning team sits at the intersection of cutting-edge research and production systems, transforming raw audio into high-signal data for leading AI labs and enterprises. We own the full ML lifecycle - from researching novel speech processing algorithms to deploying models processing terabytes of audio daily.
About this role
As a ML Research Engineer at David AI you'll build cutting-edge speech and audio models, production inference systems and resilient pipelines that showcase what high-quality data can really do.
In this role, you will
Research, design, and implement solutions using advanced signal processing. algorithms and cutting edge ML models with application to speech and audio.
Develop production-grade inference algorithms, pipelines, and APIs with cross-functional teams that unlock key insights into our data for our customers.
Collaborating with our Operations team to gather useful training and evaluation datasets to improve the quality of our models.
Architect systems that enable resilient, durable inference and evaluations.
Your background looks like
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 and proficiency with deep learning frameworks such as PyTorch.
Ability to translate research papers and ideas into high-quality, production-ready code.
Experience deploying ML systems for production inference with cloud technologies.
Track record of setting ML roadmaps, influencing technical direction, and prioritizing research and infrastructure investments.
Ability to assess model quality in the context of user experience and business value.
Bonus points if you have
PhD or Masters in Computer Science or a related field.
Experience training large neural network models in academic or industry settings.
Expertise in audio signal processing both classical and machine learning techniques.
Experience in publishing in top conferences such as NeurIPS, ICML, ICLR, CVPR, etc.
Benefits
Unlimited PTO.
Top-notch health, dental, and vision coverage with 100% coverage for most plans.
FSA & HSA access.
401k access.
Meals 2x daily through DoorDash + snacks and beverages available at the office.
