This role is for one of the Weekday's clients

Min Experience: 5 years

Location: Bengaluru, Pune

JobType: full-time

We are looking for a skilled AI/ML Engineer to design, build, and deploy production-grade AI solutions with a strong focus on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. In this role, you will work closely with software and machine learning engineers to deliver scalable, secure, and high-impact AI applications used in real-world business environments.

This position is ideal for someone who combines strong software engineering fundamentals with hands-on experience in modern AI/ML systems and enjoys working at the intersection of research and production.

• Design and develop scalable AI/ML solutions with emphasis on LLMs, RAG pipelines, and deep learning architectures.
• Own the end-to-end AI lifecycle including data ingestion, preprocessing, embedding generation, retrieval, model training, fine-tuning, evaluation, and production deployment.
• Build and optimize RAG systems using vector databases and retrieval frameworks to deliver accurate, grounded, and explainable AI outputs.

• Apply fine-tuning techniques such as LoRA and Q-LoRA to adapt large models for domain-specific use cases.
• Implement and experiment with reasoning models and hybrid RAG + reasoning workflows for complex enterprise scenarios.
• Evaluate and improve AI and RAG systems using metrics such as retrieval accuracy, relevance, faithfulness, latency, and hallucination reduction.
• Optimize inference performance through embedding tuning, reranking strategies, compute optimization, and efficient resource utilization.

• Build and maintain MLOps / LLMOps pipelines for model training, deployment, monitoring, drift detection, and continuous improvement.
• Deploy AI solutions across cloud platforms (AWS, Azure, GCP), with exposure to edge deployments where applicable.
• Develop APIs and microservices to integrate AI and RAG capabilities into enterprise applications.
• Ensure compliance with data security, privacy, regulatory standards, and responsible AI practices.

• Collaborate with product, engineering, and business stakeholders to translate requirements into AI-driven solutions.
• Mentor junior engineers and promote best practices in AI system design and software engineering.
• Stay up to date with emerging research and advancements in LLMs, RAG, and applied AI.

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Engineering, or a related field.
• 5–8 years of hands-on experience in AI/ML engineering or related roles.
• Strong proficiency in Python.
• Solid understanding of machine learning fundamentals and deep learning concepts.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Practical experience or strong familiarity with LLMs, transformer-based architectures, and RAG concepts.

• Experience with vector databases (FAISS, Pinecone, Weaviate, Milvus).
• Familiarity with retrieval frameworks such as LangChain or LlamaIndex.
• Understanding of RAG evaluation techniques, prompt engineering, and grounding strategies.
• Exposure to frontend technologies such as React.

• AI / Machine Learning
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Python
• PyTorch / TensorFlow
• Vector Databases
• MLOps / LLMOps
• Cloud Platforms (AWS / Azure / GCP)