Machine Learning Engineer (Audio & Signal Processing)

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: W2

We 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.