AI/ML Engineer - GenAI

About the Role :

We are looking for a hands-on AI/ML (GenAI) Engineer with experience in building, fine-tuning, evaluating, and deploying LLM-powered systems. The role involves working on LLM training and evaluation pipelines, Agentic AI systems, RAG architectures, vector search, and offline/on-premise AI deployments.

Key Responsibilities : LLM Training & Evaluation :

• Build pipelines for SFT (Supervised Fine-Tuning), DPO (Direct Preference Optimization), and evaluation benchmarking.

• Develop automated evaluation frameworks and test harnesses.

• Perform regression testing and diagnose model issues.

Agentic AI System Development :

• Design agent workflows, planning loops, tool usage, and memory systems.

• Develop multi-step reasoning and AI automation systems.

• Implement prompt engineering and evaluation strategies.

RAG & Vector Search :

• Design and develop RAG pipelines, including ingestion, chunking, and embeddings.

• Work with vector databases such as Pinecone, Weaviate, and Milvus.

• Improve retrieval performance using reranking and evaluation techniques.

Deployment & Engineering :

• Deploy AI/ML systems in offline and on-premise environments.

• Build scalable APIs and services.

• Implement monitoring, logging, debugging, and fallback mechanisms.

Collaboration :

• Collaborate with data scientists and ML engineers.

• Translate business requirements into practical AI solutions.

• Document systems, experiments, and technical implementations.

Required Qualifications :

• Bachelor's degree in Computer Science or a related field.

• 1.5 - 2 years of experience in AI/ML.

• Strong programming skills in Python.

• Hands-on experience with PyTorch, TensorFlow, or JAX.

• Experience with LLM fine-tuning and prompt engineering.

Must-Have Skills :

• Experience building Agentic AI systems and reasoning workflows.

• LangChain, LlamaIndex, LangGraph.

• Strong understanding of RAG.

• Experience building LLM evaluation pipelines.

• Understanding of Transformer models and embeddings.

• Experience deploying solutions in offline/on-premise environments.

• Familiarity with Vector Databases.

• Strong debugging and problem-solving skills.

Why Join :

• Work on advanced LLM and Generative AI systems.

• Build real-world AI solutions.

• Gain hands-on exposure to RAG, LLM evaluation, Agentic AI, and AI deployment.

• Work on challenging AI/ML engineering problems.