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Machine Learning Engineer
Tailored Management
- 🇺🇸 United States
- On-site
- 4 days ago
- Machine Learning
- Python
- PyTorch
- Pension
4 days ago
Location: Fully In-Office, 5days a week at Redmond, WA
Contract Duration: 6 months
Contract Type: Contingent Worker – W2
Pay Rate: $70 - $75 per hour on W2
Benefits: Dental, Health, Vision, 401K, PTO
Note: This is a W-2-only position. We do not offer visa sponsorship and cannot accept H-1B, F-1/STEM OPT, 1099, C2C, or C2H arrangements.
Role Overview
We are seeking aMachine Learning Engineer to own and sustain a family of production machine learning models supportingperceptual audio evaluation. This role will be responsible for the end-to-end lifecycle of ML models, including model evaluation, inference services, deployment, monitoring, troubleshooting, and integration into internal tools and workflows.
The ideal candidate combines strongPython and PyTorch skills with practicalML engineering experience and foundational knowledge ofaudio and signal processing. Experience with audio, speech, perceptual quality models, or production ML platforms is highly valued.
Top 3 Must-Have HARD Skills
- Python + Deep Learning: Proficiency inPython and a deep-learning framework such asPyTorch.
- Machine Learning + ML Engineering: Knowledge ofMachine Learning concepts and ML engineering practices, including model evaluation, inference, deployment, troubleshooting, and production ML workflows.
- Audio + Signal Processing: Basic knowledge ofaudio and signal processing sufficient to understand and troubleshoot audio-based ML models and their outputs.
- Experience withaudio, speech, or perceptual quality models, such asMOS prediction.
- Working familiarity with audio concepts includingwaveforms, sample rate, and spectrograms, sufficient to sanity-check model outputs.
- Experience with theMeta internal ML platform tooling stack or comparable internal ML infrastructure.
- Experience deploying and maintainingmachine learning models in production.
- Experience operating production services, includingon-call support, ticket queues, runbooks, access management, and escalation.
- Experience developinglightweight web front ends or integrating ML models into internal web-based tools.
- Own a family ofdeep-learning models end to end, including architecture, checkpoints, evaluation pipelines, serving infrastructure, versioning, and failure modes.
- Maintain ML models'inference services and evaluation pipelines.
- Integrate models into internal and cross-functional tools and workflows throughAPIs, service endpoints, and lightweight web interfaces.
- Operatealways-on model inference capacity, including monitoring traffic, resolving throttling issues, tuning auto-scaling, requesting additional capacity, redeploying services, and escalating issues to platform owners as needed.
- Run analysis and interpretmodel evaluation results on request.
- Apply minor bug fixes, preprocessing changes, model version updates, and checkpoint swaps.
- Support model users and tooling owners across various technical domains, includingaudio engineers, software engineers, research scientists, and technical program managers.
- Troubleshoot production issues across model, data, inference, and service layers.
- Maintain operational documentation, runbooks, and procedures for supported ML services.
- Serve ason-call support for covered production services.
- Partner with engineering, research, and platform teams to improve model reliability, scalability, and usability.
Minimum Qualifications
- Bachelor's degree inComputer 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 and take ownership of technical deliverables.
- Ability to troubleshoot and communicate technical issues across engineering and research environments.
Preferred Qualifications
- Master's or PhD inElectrical 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.
AtTailored Management, we help people get jobs and take pride in their work, so we better take pride in ours too. Not every company has the opportunity to meaningfully and directly impact individuals in a way that makes their lives tangibly better. To better support our employees, we offer a wide variety of benefit options to support you. We offer:
- Medical Coverage – HDHP, PPO, and Surest plan options
- Minimum Essential Coverage (MEC)
- Dental Insurance
- Vision Insurance
- Short-Term Disability (STD)
- Long-Term Disability (LTD)
- Life & AD&D Insurance
- Critical Illness Insurance
- Accident Insurance
- Employee Assistance Program (EAP)
Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation. #TMMT
Machine Learning Engineer · Tailored Management