- Writing production level, scalable code with Python (or scala)

- MLOps/LLMOps, machine learning engineering, Big Data, or a related role.

- Elastic search, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, MLflow, Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools.

- Distributed systems programming, AI/ML solutions architecture, Micro services architecture experience.

- Show Progressive experience as in machine learning, data engineering or similar roles.

- 2-3 years of experience with operationalising data-driven pipelines for large scale batch and stream processing analytics solutions

- Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions

Skill sets :

- Experience with SageMaker and/or Vertex AI or Azure AI Foundry or Databricks

Highly Desirable Experience :

- 6-12 months of experience working with RAG pipelines with vector databases (FAISS, Pinecone, Weaviate, etc.), prompt engineering and/or Generative AI use cases.

- Experience in CPG, Retail is preferred

- Fine-tune transformer-based models for domain-specific tasks

- Develop AI agents that can perform task chaining and tool usage (e.g., LangGraph, Auto-GPT, AgentOps)