Senior AI/ML Engineer

Metasphere; Ahmedabad District; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Metasphere in Ahmedabad is seeking a Senior AI/ML Engineer to design and deploy production-grade ML models and generative AI applications. You will work on end-to-end ML pipelines powering our platform.

You will own the full lifecycle from modeling to deployment, focusing on LLM orchestration, RAG pipelines, multi-modal AI, and MLOps, collaborating with product and engineering teams on-site.

Qualifications

• Expert-level Python with clean, testable code.
• Deep learning with TensorFlow/PyTorch and ML fundamentals.
• Experience with LLMs, Prompt Engineering, and LangChain/LangGraph.

Responsibilities

• Design, develop, and deploy production-grade ML models and Generative AI solutions spanning LLMs, RAG, and Multi-modal AI.
• Build and optimize AI agents using LangChain, LangGraph, and LangSmith to automate complex workflows.
• Architect and maintain scalable AI pipelines and RESTful services using FastAPI and Python, with MLOps for versioning and monitoring.
• Implement RAG pipelines using Vector Databases and PEFT/LoRA on foundational models.
• Conduct advanced statistical analysis and feature engineering on large datasets.
• Design data storage across SQL and NoSQL environments.
• Lead code reviews and mentor junior engineers.

Skills

Python

TensorFlow

PyTorch

LLMs

LangChain

LangGraph

FastAPI

MLOps

Tools

Qdrant

Pinecone

Weaviate

MLflow

Weights & Biases

LangSmith

Job description

Overview

We’re looking for a Senior AI/ML Engineer who’s as comfortable with production systems as with model development. You’ll go beyond training to architect agentic AI systems, generative AI applications, and ML pipelines that power our core platform.

Overview

We’re looking for a Senior AI/ML Engineer who’s as comfortable with production systems as with model development. You’ll go beyond training to architect agentic AI systems, generative AI applications, and ML pipelines that power our core platform.

You’ll own the full lifecycle of machine learning projects, from statistical modeling and feature engineering through to deploying robust APIs and monitoring performance in production. Your work will span LLM orchestration, RAG pipelines, multi-modal AI, and MLOps infrastructure, all built to production-grade standards.

This role is on-site at our Ahmedabad office. You’ll work closely with product and engineering teams, and your architectural decisions will directly shape how we build, scale, and operate AI across the platform.

Requirements

Must-have

• Expert-level Python proficiency with a focus on writing clean, testable, and efficient code.
• In-depth experience with deep learning frameworks such as TensorFlow and PyTorch, along with strong ML fundamentals including statistical modeling, classical algorithms, and evaluation metrics.
• Practical experience with LLMs (GPT, Claude, LLaMA), Prompt Engineering, and agentic frameworks like LangChain or LangGraph.

Good to have

• Hands‑on experience with Vector Databases (Qdrant, Pinecone, Weaviate) and semantic search optimization.
• Extensive experience with FastAPI for building high-performance, production-ready microservices.
• Experience with experiment tracking and model monitoring platforms such as MLflow, Weights & Biases, or similar MLOps tooling.

What you'll do

• Design, develop, and deploy production-grade ML models and Generative AI solutions spanning LLMs, RAG, and Multi-modal AI.
• Build and optimize AI agents using frameworks like LangChain, LangGraph, and LangSmith to automate complex business workflows.
• Architect and maintain scalable AI pipelines and RESTful services using FastAPI and Python, implementing MLOps best practices for model versioning, monitoring, and retraining.
• Implement Retrieval-Augmented Generation (RAG) pipelines using Vector Databases and perform parameter-efficient fine-tuning (PEFT/LoRA) on foundational models.
• Conduct advanced statistical analysis and feature engineering on large‑scale structured and unstructured datasets.
• Design and optimize data storage solutions across SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) environments.
• Apply software design patterns and robust data structures to ensure code is maintainable, repeatable, and efficient.
• Lead code reviews, mentor junior engineers, and advocate for engineering best practices across AI initiatives.

Skills

PythonMachine Learning LLMsFastAPI TensorFlowPyTorchRAGVector Databases