Python AI / ML Professional - GenAI

Job Title: Python, Machine Learning & GenAI Specialist

Job Summary

We are seeking a dynamic and experienced professional with 5+ years of hands-on expertise in Python, Machine Learning, and advanced experience in Deep Learning and Generative AI (GenAI). This role is ideal for candidates passionate about solving complex problems, driving innovation, and implementing next-gen AI solutions for real-world applications.

Key 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.

Required Skills & 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.

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.