At a Glance
- Tasks: Own and maintain cutting-edge machine learning models for audio applications.
- Company: Join a leading tech firm focused on innovation and collaboration.
- Benefits: Competitive hourly rate, onsite work, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement potential.
- Why this job: Make an impact in the audio tech space while working with advanced ML technologies.
- Qualifications: Bachelor's degree in a relevant field and proficiency in Python and ML frameworks.
The predicted salary is between 80 - 80 $ per hour.
Location: Redmond, WA | Sunnyvale, CA - ONSITE Role
Summary: Own and sustain a family of production machine learning models. Day to day responsibilities include: maintain ML models' inference services and evaluation pipelines, integrate models into internal tools, and support the users and tooling owners using models.
Tech Stack: Python, PyTorch, Jupyter/Bento, Model-serving and always-on inference capacity, REST/GraphQL-style endpoints, and a lightweight web UI
Responsibilities:
- Own a family of deep-learning models end to end: architecture, checkpoints, evaluation pipelines, serving infrastructure, and failure modes
- Integrate these models into internal and XFN tools and workflows via API/endpoint integration and web UI onboarding.
- Operate always-on model inference capacity: monitor traffic, resolve throttling, tune auto-scaling, request additional capacity, redeploy, and escalate to platform owners as needed
- Run analysis and interpret model evaluations on request, apply minor bug fixes and preprocessing changes, and manage version bumps and checkpoint swaps
- Communicate with and support model users and tooling owners across various domains including audio engineers, SDEs, research scientists, TPMs etc.
- Serve as oncall for the covered services.
Minimum Qualifications:
- Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
- Proficiency in Python and a deep-learning framework such as PyTorch.
- Knowledge of Machine Learning concepts and ML engineering practices.
- Basic knowledge of audio and signal processing.
- Ability to work independently.
Preferred Qualifications:
- Master's or PhD degree in Electrical Engineering, Audio Engineering, Speech or Signal Processing, Acoustics, Computer Science, or a related technical field.
- 2+ years of hands-on experience deploying and maintaining machine learning models in production.
- Experience operating production services, including oncall, ticket queues, runbooks, access management, and escalation.
- Working familiarity with audio concepts (waveforms, sample rate, spectrograms) sufficient to sanity-check model outputs.
- Excellent communication skills with non-ML audience, including audio engineers and scientists.
- Experience with audio, speech, or perceptual quality models (e.g. MOS prediction).
- Experience developing lightweight web front ends.
Must-Have Hard Skills: Python (PyTorch), ML Concept & Engineering Practices, Audio & Signal Processing
Good-to-Have Skills: Audio/Speech/Perceptual Quality Models, Audio concepts like waveforms, spectrograms, sample rate
Interview Process: 2 Rounds [Technical + Behavioral/Discussion on past projects]
Audio Software Engineer II # 26-25179 in Redmond employer: Us Tech Solutions
At US Tech Solutions, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to thrive. As a UX Researcher IV, you'll have the opportunity to work at the forefront of augmented and virtual reality, contributing to transformative projects while enjoying comprehensive benefits and professional growth opportunities. Our commitment to diversity and inclusion ensures that every voice is heard, making it an exciting place for passionate individuals looking to make a meaningful impact.
