Audio Software Engineer II # 26-25179
$70 - $80 per hourTemporary
US Tech Solutions
Contract Duration: 12 Months
Role Description: 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.
- Bachelors 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
- Masters 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 nonML audience including audio engineers and scientists.
- Experience with audio speech or perceptual quality models (e.g. MOS prediction)
- Experience developing lightweight web front ends
Note:
- 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
Required Experience:
IC
Vacancy posted 14 days ago
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