Machine Learning Engineer (Audio & Signal Processing)

Posted 5 days ago

intelliswift an ltts companyRedmond (WA)

Computer Systems Engineers/Architects Computer Systems Design Services

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About the role

Job Title: Software Engineer II – Machine Learning Engineer (Audio & Signal Processing)

Location: Redmond, WA (Onsite 5 days/week)

Duration: 9 Months (Potential to extend to long term)

Contract: W2We are seeking a Machine Learning Engineer to support and maintain production-grade machine learning models focused on audio quality evaluation and perceptual audio analysis. This role combines machine learning engineering, model operations, infrastructure support, and cross-functional collaboration. The ideal candidate has hands-on experience deploying and maintaining ML models in production environments, strong Python and PyTorch skills, and a foundational understanding of audio and signal processing concepts.

Responsibilities: Own and support a portfolio of deep learning models throughout their lifecycle, including model architecture, checkpoints, evaluation pipelines, deployment, and monitoring. Maintain and optimize model inference services and production ML workflows. Integrate machine learning services with internal tools and applications through APIs and user-facing interfaces. Monitor model performance, troubleshoot issues, manage deployments, and support service scalability. Analyze model evaluation results and implement improvements, bug fixes, and preprocessing updates. Manage model versioning, checkpoint updates, and release processes. Collaborate with software engineers, researchers, technical program managers, and domain experts to support model users. Participate in operational support and on-call rotations for deployed services. Document workflows, troubleshooting procedures, and best practices.

Minimum Qualifications: Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience. Strong programming skills in Python. Experience with deep learning frameworks such as PyTorch. Understanding of machine learning concepts and ML engineering best practices. Basic knowledge of audio and digital signal processing. Ability to work independently and manage multiple priorities.

Preferred Qualifications: Master's or PhD in Computer Science, Electrical Engineering, Audio Engineering, Signal Processing, Speech Processing, Acoustics, or related field.2+ years of experience deploying and maintaining machine learning models in production environments. Experience operating production services, including monitoring, incident response, troubleshooting, and capacity management. Familiarity with audio concepts such as waveforms, sample rates, frequency analysis, and spectrograms. Experience with audio, speech, acoustic, or perceptual quality evaluation models. Experience building and consuming RESTful APIs. Experience developing lightweight web-based tools or interfaces. Strong communication skills and ability to work with both technical and non-technical stakeholders.

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