Applied Audio ML Engineer sf, ca
ESRhealthcare and EXEC STAFF RECRUITERS- Location
- Location not stated
- Workplace
- —
- Employment
- —
- Salary
- USD 190–260/hr
Applied Audio ML Engineer sf, ca ESRhealthcare and EXEC STAFF RECRUITERS | Career Page
Applied Audio ML Engineer sf, ca
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Job Description
Applied Audio ML Engineer
Location
San Francisco
Employment Type
Full time
Location Type
On-site
Department
Engineering
Compensation
$190K – $260K Offers Equity
About this role
As an Applied ML 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 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 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 generative AI models.
Expertise in audio signal processing both classical and machine learning techniques.
Working Place
San Francisco, California, United States
Company
ESR Healthcare
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Skills
- Machine Learning
- Python
- Deep Learning
- PyTorch
- Generative AI
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