Senior Software Engineer, AI

Stryker; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Stryker, located in Gurugram District, India, is looking for a qualified candidate to design and implement AI-powered applications using advanced technologies such as Generative AI and Machine Learning.

The ideal candidate will have a Bachelor's or Master's degree with relevant experience, strong skills in Python, and familiarity with machine learning frameworks like PyTorch or TensorFlow. This role offers the opportunity to work with cutting-edge AI solutions and collaborate with cross-functional teams.

Qualifications

• Bachelor's Degree in a relevant field with 3+ years of experience, or a Master's Degree.
• Strong programming skills in Python.
• Experience with machine learning and deep learning frameworks.

Responsibilities

• Design, develop, and deploy AI-powered applications.
• Build scalable backend services and APIs for AI solutions.
• Train and deploy machine learning models.

Skills

Python programming

Machine Learning

Deep Learning

Computer Vision

API development

Cloud platforms (Azure, AWS, GCP)

Education

Bachelor's or Master's in relevant field

Tools

PyTorch

TensorFlow

Docker

Kubernetes

Job description

What You Will Do

• Design, develop, and deploy AI-powered applications leveraging Generative AI, Large Language Models (LLMs), Computer Vision, Machine Learning, and Agentic AI technologies.
• Build scalable backend services, APIs, and workflow orchestration components for AI solutions.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines, intelligent assistants, and workflow automation solutions.
• Develop Computer Vision and OCR solutions for image analysis, document digitization, information extraction, and automation workflows.
• Train, optimize, evaluate, and deploy machine learning and deep learning models for production use.
• Build data pipelines supporting AI model training, validation, and inference workflows.
• Develop cloud-native AI applications and deploy solutions on Azure and other cloud platforms.
• Implement MLOps best practices including model versioning, monitoring, CI/CD, and deployment automation.
• Collaborate with cross-functional teams to translate business and clinical requirements into scalable AI solutions.
• Create technical documentation, architecture diagrams, validation reports, and deployment artifacts.
• Stay current with advancements in AI, Computer Vision, LLMs, and Agentic AI.

What You Will Need

Required Qualifications

• Bachelor's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Electrical Engineering, or a related field with 3+ years of relevant industry experience; OR
• Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Electrical Engineering, or a related field.
• Strong programming skills in Python.
• Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Experience developing APIs, backend services, and distributed applications.
• Familiarity with Computer Vision techniques including OCR, image classification, segmentation, and object detection.
• Understanding of LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), and Agentic AI concepts.
• Experience working with structured and unstructured data and building data pipelines.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Knowledge of databases, version control systems, CI/CD pipelines, and software development best practices.
• Familiarity with Docker, Kubernetes, and MLOps concepts.

Preferred Qualifications

• Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning, or similar AI platforms.
• Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent AI frameworks.
• Experience building production-grade GenAI, RAG, OCR, or intelligent document processing solutions.
• Experience with MLflow, monitoring tools, and model lifecycle management.
• Exposure to healthcare, medical imaging, or regulated environments.
• Experience creating technical architecture documentation and contributing to solution design discussions.