Über diese Senior Engineer Stelle bei Stryker
Stryker · Vor Ort · Bengaluru, India
Work Flexibility: Hybrid or Onsite
What You Will Do
Core Responsibilities
Required Qualifications
Preferred / Strongly Desired Qualifications
AI / ML & GenAI
Vocera, now part of Stryker, is looking for a highly skilled and hands-on Senior Engineer – AI/ML to join our AI platform and speech applications team. In this role, you will design, build, and scale AI-driven solutions that power real-time speech, voice, and GenAI capabilities across Stryker’s clinical communication platforms.
This is a hands-on engineering role for someone who has a strong understanding of modern AI/ML models, is fluent in Python, and has deep experience building and operationalizing AI systems on Microsoft Azure.
This is a hands-on engineering role for someone who has a strong understanding of modern AI/ML models, is fluent in Python, and has deep experience building and operationalizing AI systems on Microsoft Azure.
What You Will Do
Core Responsibilities
- Design, develop, and deploy AI/ML-powered applications with a focus on speech, language, and GenAI use cases.
- Integrate and operationalize speech-to-text, text-to-speech, NLP, and LLM-based models into production-grade backend services.
- Build and maintain cloud-native AI pipelines on Azure, including model deployment, scaling, monitoring, and cost optimization.
- Develop AI-driven features such as:
- Voice transcription and real-time speech processing
- Intent detection and entity extraction
- Conversational AI and virtual assistants
- Summarization, semantic search, and RAG-based workflows
- Fine-tune and adapt models for domain-specific vocabulary, accents, noisy environments, and healthcare contexts.
- Collaborate closely with backend engineers, product owners, UX teams, and platform teams to deliver end-to-end AI features.
- Make independent architecture and design trade-off decisions across multiple components and services.
- Drive engineering best practices around testing, reliability, observability, and security for AI systems.
- Contribute to technical documentation, design reviews, and architecture discussions.
- Participate in customer-facing discussions (Voice of Customer) to align AI solutions with real-world usage and feedback.
- Actively contribute to innovation through patents, invention disclosures, or internal IP creation.
- Mentor junior engineers and raise the overall AI/ML engineering maturity of the team.
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, or a related field.
- 3-10 years of experience in software engineering with significant hands-on work in AI/ML systems.
- Strong proficiency in Python, with experience building production-grade ML or AI services.
- Solid understanding of machine learning, NLP, and modern AI model architectures, including LLMs.
- Experience deploying and operating AI workloads on Microsoft Azure.
- Strong engineering fundamentals: system design, APIs, data pipelines, scalability, and reliability.
Preferred / Strongly Desired Qualifications
AI / ML & GenAI
- Hands-on experience with LLMs, NLP pipelines, RAG architectures, prompt engineering, and model evaluation.
- Experience integrating or fine-tuning speech models (ASR/TTS) for real-world applications.
- Familiarity with frameworks and tools such as Azure OpenAI, Azure ML, LangChain, MLflow, PyTorch, and TensorFlow.
- Exposure to sentiment analysis, intent recognition, semantic search, or conversational AI.
Cloud & Platform
- Strong experience with Azure services, such as:
- Azure OpenAI
- Azure ML
- Azure Functions / Container Apps
- Azure AI Search
- Storage, monitoring, and security services
- Experience designing cloud-native, scalable, and secure architectures.
- Familiarity with Docker, Kubernetes, CI/CD, and ML lifecycle management.
- Exposure to AWS or GCP is a plus.
Engineering & Collaboration
- Experience integrating third-party APIs and AI services.
- Background in Java-based backend systems is a plus.
- Strong documentation, design review, and cross-team collaboration skills.
- Comfortable working in an Agile development environment.
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