Engineer Associate Staff, Applied Research Science

Overview

Join Shure's Signal Processing and Applied Research Science team as an Associate Staff Engineer and help shape the future of audio technology.

In this dynamic role, you'll drive innovation by developing advanced AI / ML algorithms and cutting-edge signal processing solutions that elevate the performance of Shure products. You'll collaborate across disciplines—working closely with software engineers, data scientists, signal processing experts, and test engineers—to bring breakthrough technologies to life. Your work will span from concept to integration, partnering with teams across the company to ensure seamless implementation and long-term success.

If you're passionate about pushing the boundaries of audio through intelligent systems and creative problem-solving, we'd love to hear from you.

This position can be remote from anywhere in the U.S. but high preference to someone who can be local to the Niles, IL HQ!

Responsibilities

• Work as part of a cross-functional team to create, design & implement cutting-edge audio features and products
• Collaborate with colleagues, other engineers, and product managers to identify and document performance metrics and architectural options
• Brainstorm with colleagues, stakeholders, and other engineers to identify valuable use cases for Shure customers empowered by AI / ML and optimize platform solutions
• Design custom machine learning models and algorithms targeting audio functionality (single and multi-channel audio processing algorithms, speech enhancement, music enhancement, audio classification, etc.) within latency / computation constraints. Transform and optimize models to support implementation requirements. Work with Software Engineers to identify and optimize input features, frame rates, model structures, and other characteristics that impact algorithmic performance.
• Measure model / algorithm performance against identified metrics and fine-tune to optimize outcomes. Conduct subjective listening tests to balance results with objective results.
• Identify and collect relevant data to create robust training and test datasets, including purchase / license opportunities, in-house collected data, and simulation of algorithms within predefined audio paths
• Utilize machine learning and advanced DSP approaches to address challenges such as processing real-time, low latency data pipelines and right-sizing solutions
• Survey literature and conduct original research and experiments to solve problems. Share findings and prototypes with colleagues, senior staff, and executives
• Record findings, results, and notes in collaborative documentation tools, either independently or in collaboration with the team
• Contribute to intellectual property, participate in brainstorming, and encourage innovation in the group
• Mentor, coach, and monitor the work of less experienced engineers
• Utilize in-house annotation tools and / or third-party partners
• Adopt mature machine learning software engineering practices (e.g. shared toolkits, repos, experiment tracking)
• Track industry / academia progress, attend training / conferences, and integrate advancements into work
• Participate in Working Groups : collaborate to solve specific problems, sometimes tangential to your expertise

Qualifications

Bachelor's degree in electrical engineering, computer science, mathematics, statistics, physics, data science, machine learning or field related to research science; with minimum 8 years of related experience

Proficiency in programming languages : Python required; C / C++ or Matlab also preferred

Knowledge or experience with classical Digital Signal Processing

Note : The employer may provide information about the company for context, but does not require you to include extraneous corporate boilerplate or promotional content beyond what is necessary to describe the role and requirements.

EEO statement : Applicants for this position must be currently authorized to work in the United States on a full-time basis.

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