The Role
Build and scale production machine learning systems for ecommerce search, retrieval, ranking, recommendations, personalization, and GenAI experiences. Responsibilities include developing ML models, optimizing multi-stage ranking pipelines, running offline and A/B experiments, applying reinforcement learning and bandits, deploying Databricks pipelines through AKS, designing scalable ML infrastructure, and monitoring models using MLOps and LLMOps practices.
Summary Generated by Built In
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.
Core Responsibilities
Design, build, and improve ML models for:
- Product matching / entity resolution
- Semantic retrieval and search relevance
- 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
Requirements
Required Qualifications
5–8+ years of experience in ML Engineering / Applied AI
Strong experience with:
Search, retrieval, and ranking systems
NLP / embeddings / deep learning models
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
Preferred Qualifications
Master’s degree in Computer Science or related field (preferably in NLP or Computer Vision)
Experience with:
Multi-stage ranking systems (search/recommendation engines)
Reinforcement learning / bandits
GenAI, LLMs, and agentic frameworks (LangChain, LangGraph, etc.)
Ecommerce or marketplace domains
Familiarity with:
Modern data platforms (Snowflake, Data Lakes)
MLOps/LLMOps tools (MLflow or similar)
AI governance (evaluation, explainability, safety)
Skills Required
- 5-8+ years of experience in ML Engineering or Applied AI
- Strong experience with search, retrieval, and ranking systems
- Strong experience with NLP, embeddings, and deep learning models
- Experience with experimentation and evaluation methodologies
- Track record of building production-grade ML systems
- Strong proficiency in Python
- Hands-on experience with Databricks
- Hands-on experience with Kubernetes-based deployment; AKS preferred
- Ability to learn quickly and operate independently
- Master's degree in Computer Science or a related field, preferably NLP or Computer Vision
- Experience with multi-stage ranking systems, search engines, or recommendation engines
- Experience with reinforcement learning or bandits
- Experience with GenAI, LLMs, or agentic frameworks such as LangChain or LangGraph
- Experience in ecommerce or marketplace domains
- Familiarity with Snowflake or modern data platforms and data lakes
- Familiarity with MLOps or LLMOps tools such as MLflow
- Familiarity with AI governance, evaluation, explainability, or safety
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The Company
What We Do
Staples India is Staples’ technology and innovation hub in Chennai, building platforms, systems, and digital solutions that support the company’s global operations and future of work. Staples serves consumers and businesses with workplace products and services, including office supplies, janitorial products, technology, furniture, breakroom essentials, print and marketing, shipping, travel, and promotional offerings. Its India teams focus on engineering, eCommerce, process optimization, and enterprise solutions.
