Founding Applied ML Engineer
David AI
Taro Hiring Bonus Eligible
Receive a cash bonus of up to $15,000 when you successfully land this role. You can view your bonus here.
Job Description
David AI is pioneering audio data research, committed to bridging the gap between AI and the real world through high-quality audio data. As an Applied ML Engineer, you will develop cutting-edge speech and audio models, and build resilient production inference systems. Your responsibilities include researching advanced signal processing algorithms, developing production-grade APIs, and collaborating with the Operations team to improve model quality. You will architect resilient inference and evaluation systems, and drive the ML roadmap.
David AI is rapidly growing and backed by First Round Capital, Y Combinator, and SV Angel. Benefits include a competitive salary and equity package, flexible PTO, comprehensive health, dental, and vision coverage, paid lunch and dinner, and 401k access. This is an exciting opportunity to join a sharp, ambitious team and influence the technical direction of audio AI.
Responsibilities
- Research, design, and implement solutions using advanced signal processing algorithms and bleeding 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 data for customers
- Collaborate with Operations team to gather useful training and evaluation datasets to improve the quality of models
- Architect the systems that enable resilient, durable inference and evaluations
- Have full autonomy to drive the ML roadmap, influence technical direction, and lead research and infrastructure investments
Requirements
- 5+ years of professional ML experience including DSP/ML audio algorithm development
- Demonstrated experience owning ML pipelines end-to-end, from POC to production
- Ability to translate research ideas or papers into high-quality Python code
- Proficiency in Python and common Deep Learning frameworks like PyTorch
- Ability to think broadly and cross-functionally about model quality in the context of user experience and the business value
- Experience working with cloud technologies (eg. AWS or GCP) and developing machine learning models in a cloud environment
- PhD or Masters in Computer Science or a related field
- Experience training generative AI models
- Expertise in audio signal processing, both classical and machine learning techniques
- Led ML teams, setting direction and driving development cadence
Benefits
- Rapid Career Growth
- 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
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