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.

Requirements

Master’s degree in Electrical Engineering, Computer Science, Mathematics, Statistic, Physics, Data Science, Machine Learning, Music Technology or field related to research science
PhD in Electrical Engineering, Computer Science, Mathematics, Statistic, Physics, Data Science, Machine Learning, Music Technology or field related to research science
Proficiency in programming languages: Python required; C/C++ or Matlab also preferred
Proficiency in leveraging frameworks and libraries including: PyTorch, Tensorflow, scikit-learn, NumPy, Matplotlib, etc.
Proficiency in tools and technologies including: Git/GitHub, Docker, Jupyter Lab, AWS, OnPrem GPU training tools
Knowledge or experience with Speech enhancement algorithms
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.

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

Applicant Tracking System Keywords

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

Hard Skills & Tools

PythonC/C++MatlabPyTorchTensorflowscikit-learnNumPyMatplotliblow latency solutionsaudio processing algorithms

Soft Skills

collaborationproblem-solvingcommunicationinnovationresearchdocumentationbrainstormingperformance optimizationdata analysisteamwork

Certifications

Master’s degree in Electrical EngineeringMaster’s degree in Computer ScienceMaster’s degree in MathematicsMaster’s degree in StatisticsMaster’s degree in PhysicsMaster’s degree in Data ScienceMaster’s degree in Machine LearningMaster’s degree in Music TechnologyPhD in Electrical EngineeringPhD in Computer Science