ML Engineer - Perceptual Audio (Production)

Apex Systems, LLC; Redmond (WA); On-site; USD 80,000 - 94,000; Full time

Benefits offered by this job

Health insurance

401K program

Employee stock purchase program (ESPP)

Health Savings Account (HSA)

Job summary

Everforth Apex Systems seeks a Software Engineer II in Redmond to own end-to-end management of deep-learning models, including architecture, evaluation pipelines, and serving infrastructure. You will integrate models into internal tools via APIs and provide onboarding through web UIs.

The role requires Python and PyTorch proficiency, ML concepts knowledge, and audio processing basics. On-call rotations and collaboration with audio engineers, SDEs, and researchers are part of the job.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, or related field
• 2+ years of hands-on experience deploying and maintaining ML models in production
• Proficiency in Python and PyTorch
• Foundational knowledge of ML concepts and audio processing
• Experience with on-call rotations, runbooks, and escalation procedures

Responsibilities

• Own the end-to-end management of deep-learning models, including architecture, checkpoints, evaluation pipelines, serving infra, and failure modes
• Integrate models into internal tools and workflows via API/endpoint integration and web UI onboarding
• Operate always-on model inference capacity, monitor traffic, resolve throttling, tune auto-scaling, redeploy, and escalate issues
• Run analysis and interpret model evaluations, apply minor bug fixes, manage version updates, and handle checkpoint swaps
• Communicate with model users and tooling owners across domains including audio engineers, SDEs, researchers, and TPMs
• Provide on-call support for the covered services

Skills

Python

PyTorch

Deep learning

ML engineering

Audio processing

Education

Bachelor's degree in Computer Science, Electrical Engineering, or related field

Job description

Everforth Apex Systems seeks a Software Engineer II in Redmond to own end-to-end management of deep-learning models, including architecture, evaluation pipelines, and serving infrastructure. You will integrate models into internal tools via APIs and provide onboarding through web UIs.

The role requires Python and PyTorch proficiency, ML concepts knowledge, and audio processing basics. On-call rotations and collaboration with audio engineers, SDEs, and researchers are part of the job.