Job Summary
Experience:
5.00 - 7.00 Years
Industrial Type:
IT-Software/Software Services
Location:
Chennai
Functional Area:
IT Software - Other
Designation:
Senior AI Engineer - G3 - ST
Key Skills:
Gen AI, Machine Learning Engineering, ML Model
Educational Level:
Graduate/Bachelors
Job Post Date:
2026-04-02 13:06:35
Stream of Study:
Degree:
BCA, BE-Comp/IT, BE-Other, BSc-Comp/IT, BSc-Other, BTech-Comp/IT, BTech-Other, MCA, ME-Comp/IT, ME-Other, MSc-Comp/IT, MS-Comp/IT, MSc-Other, MS-Other, MTech-Comp/IT, MTech-Other
Company Description
We’re more than simply paper, ink, and toner. We provide the supplies and services that thousands of businesses around the world need to succeed. We’re the experts in technology and conferencing equipment, cleaning products, furniture, and even breakroom items like snacks and coffee, too. (After all, innovation requires plenty of fuel!) This is a company of more than 13,000 smart, insightful experts who believe in the power of what can be and are driven to make business easier for our customers.
Job Description
Role Overview
We are hiring a Senior AI Engineer / Applied Scientist to build and scale ML systems powering ecommerce search, retrieval, and personalization. This is an 80% ML Engineering role focused on production systems, rapid experimentation, and measurable business impact.
You will own end-to-end AI solutions across matching, retrieval, ranking, and GenAI-powered experiences, from prototyping to deployment at scale.
Required Qualifications
• 5–8+ years of experience in ML Engineering / Applied AI
• Strong experience with:
o Search, retrieval, and ranking systems
o NLP / embeddings / deep learning models
o Experimentation and evaluation methodologies
• Proven track record of building production-grade ML systems
• Strong proficiency in Python
• Hands-on experience with Databricks and Kubernetes-based deployment (AKS preferred)
• Ability to learn quickly and operate independently in a fast-evolving AI landscape
Core Responsibilities
• Design, build, and improve ML models for:
o Product matching / entity resolution
o Semantic retrieval and search relevance
o Ranking and recommendation systems
• Develop and optimize multi-stage ranking pipelines (candidate generation ? ranking ? re-ranking)
• Run experimentation frameworks (offline evaluation, A/B testing) to drive continuous improvement
• Apply reinforcement learning / bandits for personalization and ranking optimization
• Build and deploy GenAI and agentic AI systems for search, discovery, and content use cases
• Productionize ML systems using Databricks-based pipelines and deploy services via AKS (Azure Kubernetes Service)
• Design scalable, reliable ML infrastructure with focus on latency, throughput, and cost efficiency
• Monitor model performance and continuously iterate using MLOps/LLMOps best practices
• Independently scope ambiguous problems and drive them from idea ? production
