About this opportunity
Stealth Startup lists this Research Scientist - Audio opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
This is a research-driven, high-impact opportunity for machine learning researchers passionate about advancing real-time AI.
As a Founding Machine Learning Research Engineer , you'll explore state-of-the-art approaches across large language models (LLMs), speech models, and multimodal AI to build human-like voice agents capable of operating in complex real-world environments.
You'll design new evaluation methodologies, prototype innovative systems, and improve reasoning, latency, and conversational intelligence. Your research will directly influence production systems, bridging cutting-edge machine learning research with large-scale deployment.
If you enjoy solving open-ended ML challenges, experimenting rapidly, and building AI systems used by thousands of customers, this role offers a unique opportunity to shape the future of conversational AI.
Key Responsibilities
Research & Experimentation
Research and develop novel techniques across LLMs, speech models, and multimodal AI.
Improve reasoning capabilities, response latency, conversational quality, and system robustness.
Explore new training paradigms, architectures, and inference techniques.
Design, train, and iterate on machine learning models and supporting pipelines.
Rapidly prototype research ideas and validate them through experimentation.
Optimize models for production performance and scalability.
Design innovative evaluation frameworks for conversational AI.
Create datasets, benchmarks, and metrics that reflect real-world customer interactions.
Measure model quality across latency, reasoning, speech quality, and user satisfaction.
Production Impact
Partner closely with engineering teams to deploy research innovations into production.
Optimize models for reliability, scalability, and operational efficiency.
Human Feedback Systems
Develop methodologies that incorporate human evaluation into model training.
Improve conversational quality through reinforcement learning and human feedback.
Build feedback loops that continuously enhance AI performance.
Stay current with cutting-edge ML research.
Evaluate emerging techniques and incorporate them into production systems.
Contribute to the long-term technical direction of AI infrastructure.
Minimum Qualifications
Strong machine learning research background in areas such as:
LLM pre-training and post-training
Speech recognition (ASR)
Deep understanding of modern machine learning architectures and algorithms.
Strong proficiency with PyTorch.
Excellent mathematical foundation in machine learning and deep learning.
Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field required.
PhD preferred, or equivalent research-level industry experience.
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.