Principal Engineer – AI / ML (Speech, Voice & GenAI Architecture)
Stryker
This listing was originally posted on Stryker's careers page. Formulate is an equal opportunity job aggregator and is not involved in the hiring process. Where salary information is estimated, it is derived from BLS industry benchmarks and may differ from actual compensation.
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Upgrade to Pro — $25/moVocera, now part of Stryker, is looking for a Principal Engineer – AI/ML to help drive the technical direction of our AI-powered voice and speech platform.
You will work closely with engineering teams to build intelligent healthcare solutions, including real-time speech recognition, AI-powered interpretation, ambient documentation, and conversational voice experiences. This is a hands-on technical leadership role focused on designing scalable AI solutions and guiding engineering teams through architecture and implementation decisions.
What You'll Do
Lead the technical architecture for AI-powered voice and speech applications.
Evaluate and recommend AI models for different use cases such as speech recognition, transcription, translation, summarization, and conversational AI.
Design and build scalable backend services using Java and Python.
Work with Azure AI services, including Azure Voice Live API, Speech Services, and Azure OpenAI.
Design low-latency, real-time speech processing pipelines.
Collaborate with product, engineering, and AI teams to deliver production-ready AI solutions.
Drive technical decisions around model selection, performance, latency, scalability, and cost optimization.
Mentor engineers and promote engineering best practices across teams.
Required Qualifications
Bachelor's or Master's degree in Computer Science or a related field.
14+ years of software engineering experience.
Strong backend development experience in Java.
Working knowledge of Python for AI/ML integration and experimentation.
Experience building cloud-based applications on Microsoft Azure or a similar cloud platform.
Experience working with AI/ML services such as speech recognition, LLMs, or conversational AI.
Good understanding of REST APIs, distributed systems, and microservices architecture.
Strong problem-solving and technical leadership skills.
Preferred Qualifications
Experience with one or more of the following is a plus:
Azure Voice Live API
Azure Speech Services
Azure OpenAI
Real-time speech transcription
Conversational AI or voice assistants
Large Language Models (LLMs)
AI model evaluation and selection
Kubernetes and containerized applications
Healthcare or enterprise software development
What We're Looking For
We're looking for someone who enjoys solving real engineering problems using AI rather than researching AI models. The ideal candidate should be comfortable evaluating different AI models, understanding their trade-offs, integrating them into production systems, and helping engineering teams build scalable, reliable AI-powered applications.
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