Python AI/ML - GenAI Professional

Tekskills Inc.

Hyderabad

On-site

INR 2,500,000 - 5,000,000

Full time

5 days ago
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Job summary

Tekskills Inc. Hyderabad is seeking an experienced AI/ML engineer to design, develop, and deploy robust Python-based ML solutions. You will build end-to-end models, optimize GenAI applications with vector databases and Langchain/LangGraph, and integrate data sources for scalable production pipelines.

The role requires 5+ years in Python and ML with TensorFlow/PyTorch/scikit-learn, strong deep learning experience, and ability to collaborate across teams to deliver cutting-edge AI features.

Qualifications

  • 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.

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.

Skills

Python
Machine learning
Deep learning
TensorFlow
PyTorch
scikit-learn
APIs

Tools

Vector Databases
Langchain
Langgraph
RAG
MCP

Job description

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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