Senior Engineer, Software Implementation (Machine Learning and Audio)

Overview

The Senior Engineer, Software (Machine Learning and Audio) is responsible for implementing audio functionality, including machine learning algorithms and Digital Signal Processing, in applications and in embedded hardware architectures for products in development as well as functional prototypes.  Part of a machine learning and artificial intelligence lab, this cross-functional role works with other teams across the company to demonstrate and incorporate emerging and forward leaning technology into Shure’s products possibly including developing innovative IoT device control chatbots with advanced agentic capabilities using natural language processing, retrieval augmented generation (RAG), and intergrating tool use and function calling within conversation AI systems.  

 

This Senior Engineer will be equally capable of optimizing the performance and implementation resources of audio machine learning implementations, contributing to the audio quality of candidate algorithms, understanding and specifying software architectures, meeting and optimizing real-time signal processing requirements. 

 

This role will be Hybrid based out of our Niles, IL Corporate HQ. 

Responsibilities

• Works closely with applied research scientists to iteratively develop, implement, and validate machine learning models for both prototyping efforts as well as product integration
• Understands machine learning research code and translates it into efficient and portable C++ inference code
• Develops tools for the ML/AI lab such as standalone applications, software libraries, profiling tools, and audio processing simulation tools that demonstrate machine learning and signal processing capabilities
• Coordinate and manage a variety of signal processing and data science implementations across hardware/software targets
• Benchmarks and optimizes CPU load, memory utilization, and latency on hardware targets
• Builds audio pipelines including pre- and post- signal processing wrapped around a machine learning network
• Analyzes and suggests changes to layers and components of neural networks to balance model performance with implementation requirements
• Suggests model performance targets and tests model performance in a signal chain containing other audio DSP blocks
• Provides fast turnaround time of new functionalities and changes and new functionalities of signal processing prototypes
• Wears multiple hats on a small team with independence and an openness to solve problems as they are discovered
• Designs and implement natural language understanding and generation components for IoT device control chatbot / agents
• Develop and integrate retrieval augmented generation (RAG) capabilities to enhance the chatbot's performance and knowledge retrieval
• Implement tool use and function calling abilities within the chatbot to enable seamless interaction with various IoT devices
• Conduct thorough testing and debugging to maintain high quality and performance standards
• Stay up-to-date with the latest advancements in conversational AI, NLP, and related technologies to continuously improve the agentic capabilities
• Stays up to date with latest advancement in software, AI/ML, and emerging technologies to contribute fresh ideas and insights to the team
• Generates intellectual property and captures inventions in disclosures for patent pursuits

Qualifications

• Masters or Bachelors in electrical engineering/DSP, computer science, computer engineering, Human-Computer Interaction or a related field
• 6+ years work experience in software development (8+ years if Bachelors only)
• Deep understanding of computational and memory architectures, its relation to efficient embedded implementation of neural networks, and compiler optimizers
• Strong proficiency in C/C++
• Strong proficiency in optimization using platform intrinsics such as Neon and AVX
• Strong proficiency with audio transforms and an ability to recommend optimal audio features for a data science problems
• Proficiency in low latency, embedded software implementations
• Proficiency with DSP fundamentals and algorithms, preferably in audio and speech enhancement, adaptive filtering, beamforming, and source separation
• Proficiency with multi-threaded system frameworks and efficient resource management
• Proficiency in software development principles and object-oriented design methodology
• Experience with machine learning frameworks such as Pytorch, Tensorflow, Tensorflow Lite, Scikit-learn, ONNX; Amazon Web Services for Artificial Intelligence and Machine Learning
• Experience with Python and porting to other languages such as C++
• Experience with developing and debugging