(Urgent Search) Principal AI/ML Engineer

2 days ago

Bengaluru, India Optum Full time

Lead innovation in deep learning, foundation models, reinforcement learning, or multimodal AI

Key Skills:

- GenAI, Python coding
- Research-level knowledge of LLMs, vision transformers (ViTs), diffusion models, RL, or multi-agent systems
- RAG & Vector Databases: Expertise in building and querying knowledge bases using Retrieval-Augmented Generation with Azure AI Search or similar technologies
- LLM Fine-Tuning: Hands-on experience with efficient finetuning techniques (LoRA/QLoRA) for specializing models on custom datasets
- Proficiency with libraries for data transformation and comparison, such as JSON Patch and DeepDiff
- Quantum Computing: Understanding of quantum algorithms and tools like IBM's Qiskit and Google's Cirq.
- Familiarity with Multimodal transformers - integrating text, image, and audio data to create models
- Experience on graph-based RAGs for contextual reasoning and incorporating knowledge connections from graph neural networks. Real time RAG systems to handle dynamic and up-to-date information
- Track record of research (papers, patents, open source)

Must have skills

- LLM & RAG Architecture Expertise:
- Hands-on experience with Retrieval-Augmented Generation (RAG) architectures using embeddings via Azure AI Search and Databricks.
- Proficient in implementing semantic search capabilities.
- Familiar with MCP servers for scalable deployment.
- Agentic AI & Orchestration: (Must have differentiating factor will be level of expertise)
- Experience with autonomous decision support using LangGraph.
- Skilled in agent orchestration using Microsoft Copilot Studio and CrewAI.
- Performance Optimization: (Must have differentiating factor will be level of expertise)
- Working knowledge of latency reduction techniques for RAG-based applications, including Redis-based caching.
- LLM Fine-Tuning: (Must have for differentiating factor will be level of expertise)
- Practical understanding of fine-tuning methods such as LoRA (Low-Rank Adaptation).
- Model Selection & Prompting: (Must have differentiating factor will be level of expertise)
- Awareness of the latest LLMs tailored to specific use cases (e.g., Claude, Gemini, GPT series).
- Understanding of prompt engineering requirements across different models.
- Cost Estimation: (Must have differentiating factor will be level of expertise)
- Ability to calculate and optimize costs for API-based model usage.
- Functional/Team experience
- Expertise with diverse AI uses cases
- Business and Domain Understanding
- Track record of research (papers, patents, open source)

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