ChatGPT Jobs · 1 day ago
Applied Research Science Engineer (Audio ML)
Niles, IL
Part-time
Hybrid
Mid, Senior Level
$90K/yr - $144K/yrShure is a leading global manufacturer of audio equipment known for quality, reliability, and durability. The Applied Research Science Engineer (Audio ML) will develop sophisticated audio solutions using AI/ML techniques, collaborating with cross-functional teams to integrate emerging technologies into Shure's product ecosystem.
Computer Software
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
Qualification
Required
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
Preferred
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
Medical
Retirement
PTO
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
Company
ChatGPT Jobs
We find the best job offers for experts in ChatGPT and related technologies.
Founded in 2024
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase