Engineer II, Applied Research Science

Shure • Niles, IL

75d • $90,000 - $144,000

About The Position

As an Engineer II, Applied Research Science within Shure’s Signal Processing and Applied Research Science team, you will play a pivotal role in shaping the future of audio technology. This position focuses on developing sophisticated customer-facing audio solutions by leveraging cutting-edge AI/ML techniques and advanced algorithmic innovations. In this cross-functional role, you’ll collaborate with experts in software engineering, signal processing, data science, and testing, as well as work closely with teams across the organization. Your mission will be to explore, prototype, and integrate emerging technologies into Shure’s product ecosystem—ensuring our solutions remain at the forefront of innovation and deliver exceptional audio experiences. This position will be hybrid out of our Niles, IL HQ!

Requirements

• Bachelor’s degree in electrical engineering, computer science, mathematics, statistic, physics, data science, machine learning or field related to research science; with minimum 2 years of related experience.
• Master’s degree in electrical engineering, computer science, mathematics, statistic, physics, data science, machine learning or field related to research science; with some project.

Nice To Haves

• Knowledge or experience with classical Digital Signal Processing.
• Proficiency in developing low latency, embedded-friendly solutions.
• Experience in Audio engineering, DAWs, recording, or other audio production.

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 and 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 pre-defined audio paths.
• Exploit 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.
• 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.
• Collaborate to solve specific problems, sometimes tangential to your expertise.

Benefits

• Comprehensive healthcare
• Mental health and retirement savings plans
• Generous paid time off programs
• Employee discounts
• Professional development opportunities
• Work-life balance initiatives
• Employee recognition programs
• Volunteering/community involvement opportunities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 1,001-5,000 employees