Machine Learning Researcher - Audio

Protege Inc.

Job Overview

Location

Remote

Job Type

Full-time

Full Job Description

📋 Description

• Lead the research and development of novel evaluation frameworks to measure audio data quality for machine learning systems, focusing on speech, audio, and multimodal models.
• Investigate how acoustic degradation, dataset inconsistency, recording conditions, speaker variation, labeling quality, segmentation errors, and signal artifacts impact downstream model performance in ASR, TTS, speaker modeling, and representation learning.
• Design and validate new metrics for direct waveform analysis, including effective bandwidth, spectral energy distribution, high-frequency roll-off, noise levels, clipping, reverberation, distortion, and codec artifacts.
• Develop segment-level quality evaluation workflows that detect localized degradation missed by file-level averages, using multiple complementary metrics to identify bandwidth mismatches, resampling artifacts, and signal distortions.
• Conduct targeted model evaluations linking specific audio quality issues to measurable changes in ASR accuracy, speaker embedding stability, speech representation quality, and synthesis fidelity.
• Identify failure modes of existing audio quality metrics and design improved alternatives that better predict downstream model behavior.
• Translate research findings into deterministic filtering rules, quality gates, and dataset selection strategies that improve consistency across training runs.
• Build scalable pipelines to apply audio quality analyses across large-scale datasets, track results over time, and make quality signals accessible to researchers, engineers, and data operations teams.
• Maintain up-to-date quality scorecards and characterization reports for Protege’s audio catalog, ensuring clear, operationalizable metrics for dataset readiness.
• Collaborate cross-functionally with ML researchers, data engineers, data operations, and external partners to define, measure, and communicate the value of Protege’s audio data assets.
• Establish a trustworthy baseline for audio quality across Protege’s datasets, using ablations and downstream model analysis to connect quality improvements to concrete performance gains.
• Operate at the intersection of research and production, formulating hypotheses, running experiments, analyzing results, and deploying scalable tools or decision rules.
• Communicate technical findings clearly through concise documentation and presentations to technical and non-technical stakeholders.
• Own end-to-end outcomes: independently scope research questions, design experiments, drive analysis, and deliver actionable insights that improve data quality standards.

🎯 Requirements

• PhD or equivalent Master’s degree + 4+ years industry experience in machine learning, audio signal processing, speech technology, computer science, statistics, engineering, or a related quantitative field
• Proven experience designing and running data evaluations, audio analyses, benchmarks, ablations, or slice-based analyses
• Strong understanding of speech/audio data and signal properties, including sampling rates, codecs, bandwidth, spectrograms, reverberation, clipping, noise, and perceptual quality
• Experience developing or critically evaluating metrics, benchmarks, or measurement frameworks for ML systems, data quality, speech technology, or audio signal analysis
• Ability to connect low-level signal properties to downstream machine learning behavior, including model accuracy, robustness, representation quality, speaker consistency, or synthesis quality
• Comfortable moving between research exploration and production implementation: formulating hypotheses, running experiments, analyzing results, and turning findings into scalable tools or decision rules

🏖️ Benefits

• Work on a generational opportunity to solve AI’s fundamental data problem
• Join a lean, fast-moving, high-trust team obsessed with velocity and impact
• Collaborate with world-class investors and ambitious AI teams powering cutting-edge models
• Operate in a culture built for those who thrive on ambiguity, own outcomes, and shape the future of data and AI
• Contribute to a platform that aims to become the ubiquitous standard for high-quality AI training data
• Embody values of integrity, resilience, velocity, kindness, candor, and shared ownership

Skills & Technologies

Remote

Degree Required

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Protege Inc.

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About Protege Inc.

Protege is a career development platform that helps early-career talent connect directly with industry mentors and secure paid apprenticeships. The company partners with employers to create short-term, project-based experiences that give participants real work opportunities while companies evaluate candidates for full-time roles. Its marketplace offers mentorship, skill-building projects, and application tools designed to reduce hiring bias and widen access to competitive industries such as tech, finance, and media. Founded in 2020 and headquartered in New York City, Protege has facilitated thousands of placements and aims to replace traditional campus recruiting with scalable experiential hiring programs.

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