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Techdome Solutions

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AI/ML Engineer

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Summary

AI/ML Engineer (5–12 yrs, office-based, immediate joiners) at Techdome Solutions who designs, trains and deploys ML models and production GenAI apps — LLM/RAG pipelines, AI agents, fine-tuning and MLOps — using Python, PyTorch/TensorFlow, LangChain/LlamaIndex and cloud platforms across Hyderabad, Indore, Noida, Delhi or Mumbai.

Job Summary

We are looking for an AI/ML Engineer to build and deploy machine learning and Generative AI solutions, from model development to production-grade AI applications.

Job Details

  • Experience: 5-12 years
  • Notice Period: Immediate joiners only
  • Locations: Hyderabad, Indore, Noida, Delhi, Mumbai, Remote
  • Employment Type: Full-time, permanent
  • Work Mode: Work from office
  • Education: B.E./B.Tech/MCA or equivalent in Computer Science, IT or a related field

Key Responsibilities

  • Design, train, evaluate and deploy ML and deep learning models for real business problems.
  • Build Generative AI applications using LLMs, including RAG pipelines, AI agents, prompt engineering and fine-tuning.
  • Work with frameworks such as LangChain, LlamaIndex and vector databases (Pinecone, FAISS, Weaviate, pgvector).
  • Develop data preprocessing, feature engineering and model training pipelines.
  • Deploy models as scalable APIs and services; set up MLOps practices for versioning, monitoring and retraining.
  • Evaluate model performance, accuracy, latency and cost, and optimise accordingly.
  • Work with product, data and engineering teams to take AI features from proof of concept to production.

Required Skills

  • 5+ years in ML/AI engineering or data science with production deployments.
  • Strong Python with scikit-learn, PyTorch or TensorFlow.
  • Hands-on experience with LLMs (OpenAI, Anthropic Claude, Llama, Mistral) and RAG architectures.
  • Experience with NLP, computer vision or predictive modelling.
  • MLOps tools such as MLflow, Kubeflow, SageMaker, Azure ML or Vertex AI.
  • Experience with Docker, APIs (FastAPI/Flask) and cloud platforms.

Good to Have

  • Model fine-tuning (LoRA/PEFT) and LLM evaluation frameworks.
  • Agentic AI frameworks (LangGraph, CrewAI, AutoGen) and MCP.
  • Experience with Spark or Databricks for large-scale data.
  • Publications, Kaggle work or open-source contributions.


Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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