AI / ML Developer

MindInventory; Ahmedabad District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

MindInventory in Ahmedabad, India is seeking an experienced AI/ML Engineer to work on cutting-edge AI-based applications. You will design and implement scalable solutions, including RAG pipelines, AI agents, and multi-agent workflows, across cloud environments.

The role requires hands-on experience with LLMs, vector databases, and popular frameworks such as PyTorch or TensorFlow, LangChain, and Docker/Kubernetes. Strong collaboration and learning mindset are essential.

Qualifications

• 3+ years of AI-based application development.
• Experience fine-tuning LLMs or domain AI models.
• Experience building production-grade AI apps using RAG or multi-agent systems.
• Familiarity with vector search and knowledge graphs.
• Experience deploying AI/ML solutions with Docker, Kubernetes and cloud services.
• Contributions to open-source AI projects or AI communities are a plus.
• Proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).
• Strong understanding of ML/DL algorithms.
• Hands-on CV techniques: image classification, detection, segmentation.
• Experience with Generative AI and LLMs (GPT, LLaMA, Mistral, Claude, Gemini).
• Experience building enterprise RAG pipelines.
• Hands-on agentic workflows with LangChain, LangGraph, LlamaIndex.
• Familiarity with no-code/low-code AI automation platforms.
• Hands-on experience with vector databases (Pinecone, Weaviate, ChromaDB, FAISS, Qdrant).
• NLP libraries (NLTK, Hugging Face, spaCy).
• Cloud platforms (AWS, Azure, GCP).
• MLOps tools (Docker, MLflow, Git, CI/CD).
• Strong analytical and problem-solving abilities.

Skills

AI/ML development

LLM fine-tuning

RAG pipelines

Vector databases

LangChain/LangGraph

Docker/Kubernetes

Python (NumPy, Pandas, Scikit-learn,Py

Tools

Docker

Kubernetes

LangChain

LangGraph

LlamaIndex

Pinecone

Weaviate

ChromaDB

FAISS

Qdrant

PyTorch

TensorFlow

Job description

Requirements

• Minimum of (3+) years of experience in AI-based application development.
• Experience fine-tuning large language models (LLMs) or working with domain-specific AI models.
• Experience building production-grade AI applications using RAG, AI agents, or multi-agent systems.
• Familiarity with Vector Search, Knowledge Graphs, and AI observability/evaluation frameworks.
• Experience deploying AI/ML solutions using Docker, Kubernetes, and cloud-native services.
• Contributions to open-source AI projects, research publications, or participation in AI communities are a plus.
• Proficiency in Python (libraries like NumPy, Pandas, Scikit-learn, and PyTorch/TensorFlow).
• Strong understanding of machine learning (ML) and deep learning (DL) algorithms.
• Hands-on experience with computer vision techniques (image classification, object detection, and segmentation).
• Practical experience with Generative AI and Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Claude, Gemini, or similar models.
• Experience building RAG (Retrieval-Augmented Generation) pipelines for enterprise applications.
• Hands-on experience building AI agents and agentic workflows using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, or similar orchestration frameworks.
• Familiarity with no-code / low-code AI automation platforms such as n8n, Dify, Flowise, or LangFlow.
• Hands-on experience with Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS, or Qdrant).
• Experience with classification tasks and building predictive models.
• Proficiency with deep learning frameworks: PyTorch and/or TensorFlow / Keras.
• Exposure to NLP techniques or libraries (NLTK, Hugging Face, spaCy).
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Familiarity with MLOps practices and tools (Docker, MLflow, Git, CI/CD).
• Strong analytical and problem-solving abilities with a passion for solving real‑world business challenges.
• Ability to translate business requirements into scalable AI and machine learning solutions.
• Excellent communication and collaboration skills for working with cross‑functional teams and clients.
• Self‑motivated learner with enthusiasm for exploring emerging AI technologies and industry trends.
• Ability to work independently while effectively managing priorities in a fast‑paced environment.
• Strong ownership mindset with attention to quality, performance, and continuous improvement.