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AI Engineer

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Onsite

AI Engineer

Kezan Consulting

AI Engineer

Skills

Google Cloud PlatformSQL QueriesDeep LearningPythonPyTorchTensorFlowMachine LearningAIAWSGitHubNLP / Natural Language ProcessingAzure

23 days ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹2,500,000 / year

Work mode:

Onsite

Published on:

30 September 2026

What they need


We are looking for a skilled AI Engineer to design, develop, and deploy AI/ML solutions that solve real-world business problems. The ideal candidate should have strong programming skills, hands-on experience with machine learning and deep learning, and familiarity with Generative AI and modern AI frameworks.

Key Responsibilities

  • Design, develop, and deploy AI/ML models for business applications.
  • Build and optimize machine learning and deep learning algorithms.
  • Work with Generative AI, LLMs, NLP, and/or Computer Vision solutions.
  • Develop AI applications using Python and relevant ML/AI frameworks.
  • Implement RAG (Retrieval-Augmented Generation) pipelines and LLM-based applications.
  • Work with vector databases and embedding models.
  • Perform data preprocessing, feature engineering, model training, evaluation, and optimization.
  • Integrate AI models into existing applications and APIs.
  • Collaborate with Data Scientists, Software Engineers, and Product teams.
  • Monitor model performance and improve accuracy, scalability, and reliability.
  • Stay updated with emerging AI technologies, tools, and research.

Required Skills

  • Strong proficiency in Python.
  • Good understanding of Machine Learning and Deep Learning concepts.
  • Experience with TensorFlow, PyTorch, Scikit-learn, or similar frameworks.
  • Hands-on experience with LLMs, Generative AI, Prompt Engineering, and RAG.
  • Knowledge of NLP and/or Computer Vision.
  • Experience with REST APIs and AI model integration.
  • Familiarity with SQL and databases.
  • Knowledge of Git/GitHub and software development practices.
  • Understanding of cloud platforms such as AWS, Azure, or GCP is preferred.

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