Principal AIML Architect

Must Have Skills
❖ Core
● 10–15 years of experience in software engineering .
● Strong programming skills in Python (mandatory).
● Experience in building production-grade ML systems (not just notebooks).
❖ AI/ML & GenAI
● Hands-on experience with:
○ Data Analysis and curation
○ Feature engineering
○ Statistical model training, evaluation & hyper parameter tuning
○ LLMs / GenAI applications
○ RAG pipeline design
○ Prompt engineering & model tuning
● Experience with frameworks like Tensorflow, PyTorch, Sci-kit, LangChain,
LlamaIndex, or similar.
● Understanding of embeddings, vector search, and retrieval systems.
● Exposure to custom model fine-tuning (good to have, not mandatory).
❖ MLOps & Deployment
● Experience with:
○ Model deployment (API-based or batch)
○ CI/CD pipelines for ML
○ Monitoring and logging
● Familiarity with tools like MLflow, Kubeflow, or similar (any one is fine).
❖ Cloud & Scalability
● Experience with at least one cloud: AWS / Azure / GCP.
● Understanding of scalable system design and APIs.
❖ Data & Systems
● Working knowledge of databases (SQL/NoSQL).
● Experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc.).

Good to Have (Optional)
● Experience in AIOps or AI for observability/use-case automation.
● Background in data engineering or analytics pipelines.
● Exposure to Kubernetes/Docker.
● Experience in telecom or high-scale product environments.