Work Flexibility: Hybrid or Onsite# **Vocera, now part of Stryker**Vocera, now part of Stryker, is seeking a highly experienced and visionary **Principal Engineer – AI/ML** to lead the architecture, strategy, and technical direction of our AI-powered speech and voice intelligence platforms.This role serves as the **AI/ML Architect** for real-time speech, conversational AI, and GenAI-driven clinical communication systems.
You will define long-term technical vision, establish scalable AI architecture patterns, and guide engineering teams in delivering reliable, secure, and high-performance AI systems deployed at enterprise scale on Microsoft Azure.This is a hands-on architectural leadership role requiring deep expertise in speech technologies, modern ML/LLM systems, distributed architecture, and cloud-native AI platforms.
## **What You Will Do**### **AI/ML Architecture & Technical Strategy*** Define and own the end-to-end AI/ML architecture for speech, voice intelligence, and GenAI platforms.
* Establish scalable patterns for real-time speech processing (low-latency ASR, TTS, streaming pipelines).
* Architect RAG-based systems, LLM orchestration layers, semantic search, and conversational AI frameworks.
* Drive design decisions across model hosting, inference optimization, observability, reliability, and cost efficiency.
* Define evaluation frameworks for model quality, accuracy, bias, hallucination control, and safety.
### **Platform & System Design*** Design enterprise-grade, cloud-native AI systems on Microsoft Azure.
* Lead architectural decisions for: + Model lifecycle management + Multi-model orchestration + Feature stores and vector databases + High-throughput inference pipelines + Secure data handling in healthcare environments* Ensure systems meet performance SLAs (latency, throughput, error rates) and compliance requirements.
* Drive multi-region scalability and disaster recovery strategy for AI workloads.
### **Speech & Voice Intelligence Leadership*** Architect solutions for: + Real-time speech-to-text and text-to-speech + Domain-adapted ASR models + Intent recognition and entity extraction + Conversational AI assistants + Summarization and contextual intelligence* Define strategies for handling accents, noisy environments, and healthcare-specific terminology.
* Guide model fine-tuning and adaptation for clinical communication use cases.
### **GenAI & LLM Systems*** Lead adoption of LLM-based architectures including: + RAG pipelines + Prompt orchestration frameworks + Guardrails and safety layers + Evaluation and monitoring systems* Define best practices for prompt engineering, model benchmarking, and production hardening.
* Drive responsible AI practices including governance, auditability, and compliance.
### **Engineering Leadership & Influence*** Provide architectural guidance across multiple pods and teams.
* Review and approve technical designs impacting AI systems.
* Mentor senior engineers and elevate AI engineering maturity across the organization.
* Partner with Product, UX, Security, DevOps, and Platform teams to align AI capabilities with business strategy.
* Participate in customer and executive discussions to translate technical vision into business value.
* Drive innovation initiatives, patents, and strategic technical investments.
## **Required Qualifications*** Bachelor's or Master's degree in Computer Science, Engineering, AI, or related field.
* 12+ years of experience in software engineering with substantial experience in AI/ML systems.
* 6+ years of experience designing and deploying production-grade AI/ML architectures.
* Deep expertise in speech technologies (ASR/TTS), NLP, and modern LLM systems.
* Strong proficiency in Python and AI frameworks (PyTorch, TensorFlow, etc.).
* Proven experience architecting AI workloads on Microsoft Azure.
* Strong background in distributed systems, backend architecture, APIs, and data pipelines.
* Demonstrated experience leading architecture decisions across multiple teams.
## **Preferred / Strongly Desired Qualifications**### **AI / ML & GenAI*** Hands-on experience with Azure OpenAI, Azure ML, and enterprise LLM deployments.
* Experience designing RAG architectures with vector databases and semantic search.
* Expertise in model evaluation frameworks, ML observability, and performance tuning.
* Experience adapting or fine-tuning speech models for domain-specific use cases.
* Familiarity with LangChain, MLflow, prompt evaluation tooling, and model governance frameworks.
### **Cloud & Platform*** Deep experience with: + Azure OpenAI + Azure ML + Azure AI Search + Azure Functions / Container Apps + Kubernetes-based model serving* Experience with CI/CD for ML systems (MLOps best practices).
* Exposure to AWS or GCP AI services is a plus.
### **Healthcare / Enterprise Systems*** Experience building secure, compliant systems in regulated environments.
* Understanding of PHI handling, data privacy, and enterprise-grade security controls.Travel Percentage: 10%
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