Machine Learning Engineer (Audio)

Machine Learning Engineer (Audio)
Location: Remote (US Only)
Duration: 12 months with potential for extension
Pay rate: $75 - $80/hr on W2
Benefits: Health, Dental, Vision, 401K, PTO
Experience: 4–5+ years
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.

About the Role

We are seeking aSoftware Engineer to support high-priority projects within an advancedResearch Audio organization. This role will focus onmachine learning model optimization, refactoring, and high-performance computing, with an emphasis on improving the efficiency and scalability of machine learning workflows.

You will work closely withresearch scientists and software engineers to streamline machine learning training and evaluation, reduce training time, improve model efficiency, and maintain well-organized, high-quality ML code.

This is an opportunity to work on technically challenging and research-oriented projects involvingaudio, speech-to-text, text-to-speech, and machine learning technologies.

Key Responsibilities

• Refactor and optimizemachine learning models and training pipelines to improve performance, efficiency, and maintainability.
• Collaborate closely withresearch scientists and engineers to translate research requirements into effective software and ML solutions.
• OptimizeGPU-based workloads and machine learning training processes to improve computational efficiency and reduce training time.
• Develop and maintain high-qualityPython and PyTorch code for machine learning workflows.
• Supportspeech-to-text, text-to-speech, and audio-related machine learning projects.
• Evaluate models and training workflows based on performance, efficiency, and other research criteria.
• Identify bottlenecks within machine learning pipelines and implement solutions to improve performance and resource utilization.
• Clean up, restructure, and organize existing machine learning codebases.
• Contribute to research-focused projects involving experimentation, iteration, and novel machine learning approaches.
• Collaborate with a small group of engineers and researchers on a daily basis while contributing to a broader research team.

Required Qualifications

• 4–5+ years of experience in software engineering, machine learning engineering, or a related technical field.
• Strong programming experience withPython.
• Hands-on experience withPyTorch.
• Professional experience working withmachine learning models, training pipelines, or ML infrastructure.
• Demonstrated experience withGPU optimization or high-performance computing for machine learning workloads.
• Experience improvingmodel performance, training efficiency, computational efficiency, or resource utilization.
• Strong software engineering fundamentals, including writing organized, maintainable, and reusable code.
• Demonstrated ability tocollaborate effectively with engineers, researchers, or other technical stakeholders.

Preferred Qualifications

• Experience working directly withresearch scientists on machine learning or software engineering projects.
• Experiencerefactoring, cleaning up, or restructuring machine learning models and codebases.
• Experience organizing and improving complexmachine learning code and infrastructure.
• Experience withspeech, audio, speech-to-text (STT), text-to-speech (TTS), or related machine learning applications.
• Experience working with large-scale or high-performanceML infrastructure.
• Experience optimizingmodel training, evaluation, inference, or GPU utilization.
• Experience working in a research-oriented or highly experimental engineering environment.

The Team & Project

The team is focused on advancingaudio and machine learning technologies through research and software engineering. Current projects involvespeech-to-text, text-to-speech, machine learning models, and research infrastructure.
You will work closely with approximately5–6 team members on a daily basis as part of a larger team of approximately 20 professionals.