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.
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)
Similar Jobs
Consumer Web • HR Tech
Design, build, and operate production-grade autonomous AI systems and multi-agent workflows. Develop agentic capabilities using OpenAI, Google Gemini, and Perplexity; implement orchestration, reflection, planning, evaluation, observability, and human-in-the-loop controls. Deploy scalable serverless services with Python and AWS, integrate with .NET systems, manage reliability and cost constraints, and create testing frameworks to monitor and improve agent quality.
Top Skills:
.NetAmazon EventbridgeAws LambdaAws Step FunctionsC#Claude CodeCursorGoogle GeminiOpenaiPerplexityPython
Software
Own end-to-end AI data engineering solutions, including architecture, ingestion, transformation, processing, metadata, quality, lineage, observability, and production operations. Build scalable pipelines and AI-ready data assets using Python, Kubernetes, Spark, PostgreSQL, Elasticsearch, and Microsoft Fabric. Develop semantic ingestion, retrieval, and LLM-assisted processing capabilities while enabling AI and agentic applications. Collaborate with researchers, standards experts, and patenting stakeholders, and provide technical guidance while remaining hands-on.
Top Skills:
SparkApache SupersetBigQueryCi/CdElasticsearchEmbeddingsKnowledge GraphsKubernetesLlmsAzureMicrosoft FabricOlapPostgresPower BIPythonSemantic RetrievalVector Search
Artificial Intelligence • Software
Design, develop, and deliver scalable full-stack applications using .NET Core, C#, Angular or React, APIs, microservices, Azure, Docker, and CI/CD. Use AI-assisted coding tools and prompt engineering to improve development, testing, debugging, and automation workflows. Implement secure authentication, authorization, and cloud-native deployments while applying clean architecture, TDD/BDD, and strong testing practices. Collaborate with clients and cross-functional teams to translate requirements into reliable technical solutions and own delivery.
Top Skills:
.Net CoreAngularAzureBddC#ChatgptCi/CdClaudeDevOpsDockerGitGithub CopilotJwtMicroservicesMstestNunitOauth2PostgresRbacReactRest ApisSaaSSQL ServerTddXunit
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
