Senior Engineer, Applied Research Science

Shure Incorporated

. Research and develop innovative AI/ML and advanced algorithmic solutions for complex customer challenges .

Posted 10/16/2026full-timeNiles • Illinois • United StatesSenior💰 $115,600 - $185,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and optimizing machine learning models and algorithms for audio applications, with a strong foundation in digital signal processing and audio engineering. Proficient in collaborating across teams to drive innovative AI/ML solutions and contribute to research and development efforts.

Highest-signal resume keywords

Machine Learning Model DevelopmentAudio Classification FrameworksPython ProgrammingDigital Signal ProcessingPrototyping and Experimentation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningAudio EngineeringAlgorithm DesignStatistical AnalysisData SimulationModel OptimizationPerformance MetricsDataset AnnotationResearch MethodologyLow-Latency Solutions

Soft Skills

CollaborationCommunicationProblem-SolvingResearch SkillsTechnical Documentation

Tools & Technologies

PyTorchTensorFlowScikit-learnNumPyMatplotlibGit/GitHubDockerJupyterAWSGPU Training Tools

Industry Keywords

AI/ML SolutionsAudio ApplicationsResearch ScienceEmbedded SystemsIntellectual Property Development

Tech Stack

Tools & technologies

AWSDockerNumpyPythonPyTorchScikit-LearnTensorflowC++

About the role

Key responsibilities & impact

Research and develop innovative AI/ML and advanced algorithmic solutions for complex customer challenges
Collaborate with software, signal processing, data, and test engineers
Research, design, and implement advanced audio features and products
Identify high-value AI/ML customer use cases and opportunities to optimize, scale, and platform solutions
Review academic and industry literature and conduct original research and experimentation
Share findings, insights, and prototypes with colleagues, senior leaders, and executives
Establish and document performance metrics, system constraints, technical requirements, and architectural options
Design and train custom machine learning models and algorithms for audio applications
Optimize models for latency, computational efficiency, and deployment requirements
Evaluate models and algorithms against performance metrics and conduct subjective listening tests when appropriate
Build prototypes using machine learning and advanced DSP techniques for real-time, low-latency data pipelines
Collect, acquire, generate, and simulate data for training and test datasets
Support dataset annotation using internal tools and third-party annotation partners
Strengthen machine learning software engineering practices through shared toolkits, code repositories, and experiment tracking
Monitor industry and academic advancements and participate in training and conferences
Participate in collaborative technical working groups
Document research methods, experiments, findings, results, and technical insights
Contribute to intellectual property development and technical brainstorming

Requirements

What you’ll need

Bachelor’s degree in electrical engineering, computer science, mathematics, statistic, physics, data science, machine learning or a field related to research science, with a minimum of 5 years of related experience
Master’s degree in the listed fields, with a minimum of 3 years of related experience
PhD in the listed fields, with no work experience required
Python required; C/C++ or Matlab preferred
Proficiency with PyTorch, TensorFlow, scikit-learn, NumPy, and Matplotlib
Proficiency with Git/GitHub, Docker, Jupyter, AWS, and on-prem GPU training tools
Experience in audio classification and scaling audio classification frameworks
Experience using AI-assisted software development and research tools
Experience independently deploying, validating, and demonstrating early proof-of-concept machine learning
Knowledge or experience with classical digital signal processing
Proficiency developing low-latency, embedded-friendly solutions
Audio engineering, recording, or other audio production experience, including DAWs
Must be currently authorized to work in the United States on a full-time basis
Shure will not sponsor work visas

Benefits

Comp & perks

Comprehensive healthcare
Mental health plans
Retirement savings plans
Generous paid time off programs
Employee discounts
Professional development opportunities
Work-life balance initiatives
Employee recognition programs
Volunteering/community involvement opportunities
Flexible work arrangements
Associate-first culture