Software Engineering - Software Engineer II - 3054592

Job#: 3054592

Job Description:

Software Engineering - Software Engineer II Location: Redmond, Washington (Onsite) or Sunnyvale CA onsite Compensation: $58 - $68 hourly

Alternate Location: Sunnyvale

Role Overview This position is for a Machine Learning Engineer focused on Perceptual Audio Evaluation. The role involves owning and sustaining a family of production machine learning models. Daily responsibilities include maintaining the inference services and evaluation pipelines of machine learning models, integrating models into internal tools, and supporting the users and tooling owners who utilize these models.

Key Responsibilities

• Own the end-to-end management of deep-learning models, including architecture, checkpoints, evaluation pipelines, serving infrastructure, and failure modes.
• Integrate models into internal and cross-functional tools and workflows through API/endpoint integration and web UI onboarding.
• Operate always-on model inference capacity by monitoring traffic, resolving throttling, tuning auto-scaling, requesting additional capacity, redeploying, and escalating issues.
• Run analysis and interpret model evaluations upon request, apply minor bug fixes, manage version updates, and handle checkpoint swaps.
• Communicate with and provide support to model users and tooling owners across various domains, including audio engineers, SDEs, research scientists, and TPMs.
• Serve as on-call support for the covered services.

Required Qualifications Education: Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.

Technical Skills: Proficiency in Python and a deep-learning framework such as PyTorch. A foundational knowledge of Machine Learning concepts, ML engineering practices, and basic audio and signal processing is required.

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 on-call rotations, ticket queues, runbooks, access management, and escalation procedures.
• Working familiarity with audio concepts such as waveforms, sample rate, and spectrograms.
• Communication skills suitable for a 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.

Compensation & Benefits A comprehensive benefits package is available to eligible employees.

Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.