Description

You will architect, fine-tune, and deploy production-grade GenAI and ML solutions, owning the end-to-end lifecycle from prototype to enterprise-scale release.

This role is on-site.

Responsibilities

• Design and implement scalable GenAI architectures using LLMs, RAG, and Transformer models.
• Build and manage LLMOps pipelines including CI/CD, automated retraining, and low-latency serving.
• Process terabyte-scale datasets using distributed computing frameworks for model training and retrieval.
• Establish rigorous evaluation frameworks for model safety, accuracy, and business impact.
• Mentor junior developers and conduct technical reviews to enforce engineering standards.

Required Skills

• 5+ years of experience in Advanced Analytics, AI, and Machine Learning.
• Proficiency in Python, PyTorch, and TensorFlow.
• Hands-on experience with LLMs, RAG, LangChain, or LlamaIndex.
• Strong expertise in MLOps and CI/CD for AI workloads.
• Advanced SQL and PySpark skills for big data processing.
• Quantitative background in Computer Science, Mathematics, or AI.
• Bachelor's degree in a relevant technical field.

Key Skills

Education

Bachelor's degree