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Perceptual Audio Engineer; Research

Job in Los Angeles, Los Angeles County, California, 90079, USA
Listing for: HARMAN International
Full Time position
Listed on 2026-10-11
Job specializations:
  • Research/Development
    AI Evaluation, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 134000 - 197000 USD Yearly USD 134000.00 197000.00 YEAR
Job Description & How to Apply Below
Position: Perceptual Audio Engineer (Research)
A Career at HARMAN

As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you’ll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day.

Introduction:

A Career at HARMAN Corporate

We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Corporate, you are integral to our company’s award-winning success.

  • Enrich your managerial and organizational talents – from finance, quality, and supply chain to human resources, IT, sales, and strategy
  • Augment your comprehensive skillset with expert training across decision-making, change management, leadership, and business development
  • Obtain 360-degree support throughout your career life cycle, from early-stage to seasoned leader
About the Role

The HARMAN Research Intelligent Audio team is working to set a new standard for audio: create experiences that understand the listener, adapt to their environment, and become more personal and useful over time. This can only be achieved when our customers can hear and experience the difference. As a Perceptual Audio Engineer in HARMAN Research, you will define what better sounds like and turn human listening into quantitative guidance for research and product decisions.

Reporting to the Director of Intelligent Audio, you will define perceptual targets, validate metrics, and build reusable evaluation methods and datasets. You will translate what people hear into practical criteria that researchers, engineers, and product teams can use. This is a hands‑on research role for someone excited to combine psychoacoustics, experimental rigor, AI tools, and real-world product impact. Success means sound quality and tuning technology is rapidly deployed into products with confidence that listeners will hear the difference.

What You Will Do
  • Define what good sounds like: Translate target user experiences into perceptual attributes and measurable success criteria.
  • Design a perceptual research program: Build an ambitious program that advances perceptual audio science while addressing clear business and product needs.
  • Develop and validate perceptual metrics: Create measures of perceived audio quality, validate them against independent listening data, and define their limits.
  • Build reusable evaluation assets: Create datasets, test methods, analysis tools, and benchmarks that other teams can trust and reuse.
  • Transfer evidence into products: Turn perceptual findings into product requirements, acceptance criteria, and regression tests in partnership with research and product teams.
  • Improve the research workflow: Use AI and automation to make perceptual research faster and more scalable without sacrificing rigor.
  • Explain practical significance: Communicate what results mean, how confident we are, and what teams should do next.
What You Need to Be Successful Essential
  • An advanced degree in acoustics, psychoacoustics, hearing science, auditory science, psychology, human factors, statistics, electrical engineering, computer science, or a related field, or demonstrated equivalent experience.

  • Significant relevant experience, typically at least five years, in perceptual audio, audio quality evaluation, or related applied research and engineering.

  • Strong command of psychoacoustics and experimental design, including sample size reasoning, controlled and blinded studies, repeated measures analysis, effect sizes, confidence intervals, reliability, and transparent treatment of exclusions and multiple comparisons.

  • Experience selecting and applying…

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