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Python AI/ML - GenAI Professional

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Onsite

Python AI/ML - GenAI Professional

Tekskills

Python AI/ML - GenAI Professional

Skills

Google Cloud PlatformDeep LearningPythonPyTorchTensorFlowGitMachine LearningAIAWSAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

20 August 2026

What they need


Job Summary

This role is ideal for candidates passionate about solving complex problems, driving innovation, and implementing next-gen AI solutions for real-world applications.

Responsibilities

  • Design, develop, and deploy robust solutions leveraging Core Python , standard libraries, and frameworks.
  • Build and optimize end-to-end machine learning and deep learning models for production use.
  • Architect and implement GenAI-powered applications utilizing Vector Databases, Langchain, Langgraph, RAG, and MCP.
  • Integrate external data sources and APIs, and build scalable pipelines for AI model deployment.
  • Collaborate with internal teams to translate business requirements into cutting-edge AI features.
  • Conduct model evaluations, fine-tuning, and support ongoing model monitoring.
  • Mentor and guide team members and contribute to best practices within the AI community.

Qualifications Required

  • Minimum 5 years of professional experience in Python development, with a focus on machine learning and deep learning.
  • Strong understanding of core ML concepts , with proven project delivery using frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Hands-on experience in deep learning (CNNs, RNNs, LLMs/Transformers, or similar architectures).
  • Demonstrable expertise in GenAI tools (Vector Databases, Langchain, Langgraph, Retrieval Augmented Generation (RAG), MCP).
  • Introductory knowledge of AI Agents and their integration in larger workflows.
  • Solid understanding of model deployment, API integration, version control, and containerization.
  • Excellent communication, problem-solving skills, and a collaborative mindset.

Preferred Qualifications

  • Experience deploying AI/ML solutions in production at scale.
  • Familiarity with cloud AI services (AWS Sagemaker, Azure ML, GCP, etc.).
  • Exposure to LLM fine-tuning, prompt engineering, or knowledge of autonomous agent systems.

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