Data Scientist / AI Engineer - GenAI & Advanced ML

Overview

Job Title: Data Scientist / AI Engineer - GenAI & Advanced ML

Experience: 2–3 Years

Location: Mumbai (On-site / Hybrid)

Role Overview

We are looking for a hands-on Data Scientist / AI Engineer with 2-3 years of experience building and deploying real-world AI/ML and LLM-driven GenAI solutions on large-scale datasets. This is a delivery focused role - the expectation is that you’ve already worked on LLM-based applications beyond prototypes and understand how to take AI systems into production.

You will work on high-scale data, production ML pipelines, and GenAI-powered features across analytics and intelligent applications.

Key Responsibilities

• Design, build, and deploy LLM-based and GenAI solutions for production use cases
• Develop RAG pipelines, LLM workflows, and AI-powered assistants
• Perform prompt engineering, model evaluation, and fine-tuning workflows
• Build and optimize advanced ML models for prediction and analytics
• Work with large-scale structured and unstructured datasets
• Develop scalable model inference and serving APIs
• Integrate AI/ML systems with product and data platforms
• Improve model performance, latency, and cost efficiency
• Collaborate with engineering and product teams to productionize AI features
• Continuously monitor and improve deployed AI systems

Required Skills

• Strong Python programming and ML ecosystem experience
• Hands-on experience building LLM and Generative AI applications
• Experience with prompt engineering, RAG architectures, embeddings, and vector search
• Experience with LLM tooling/frameworks (such as LangChain, LlamaIndex, or similar)
• Experience with vector databases (FAISS, Milvus, Pinecone, or equivalent)
• Practical experience with PyTorch or TensorFlow
• Experience working with large-scale datasets and distributed data processing
• Experience deploying ML/AI models as APIs or production services
• Strong SQL and data analysis skills
• Understanding of ML model lifecycle, evaluation, and monitoring
• Exposure to MLOps practices and experiment tracking
• Experience with cloud platforms (AWS / GCP / Azure) is preferred
• Familiarity with streaming or high-volume telemetry data systems is a plus

Ideal Profile

• Has shipped at least one LLM/GenAI solution in production or near-production
• Strong problem-solver with a build-first mindset
• Comfortable working with ambiguity and fast iteration cycles
• Focused on practical, scalable AI - not just experimental notebooks
• Clear communicator who can translate business needs into AI solutions