Data Scientist

Overview

Generative AI Developer

Key Responsibilities

Model Development & Engineering

• Build, fine-tune, and optimize

  LLMs, GPT-based models, diffusion models, and other generative architectures

  .
• Develop and deploy

  AI-powered applications

  such as chatbots, copilots, content generation tools, automated agents, and vision-based systems.
• Train custom models using organization-specific datasets.

AI Solution Design

• Understand business needs and translate them into

  AI-driven solutions

  .
• Create

  pipelines for data preprocessing, model training, evaluation, and deployment

  .
• Integrate generative AI models into existing systems and platforms.

Performance Optimization

• Optimize model inference, latency, and scalability.
• Perform

  model evaluation, A/B testing

  , and continuous improvement.

Cross-functional Collaboration

• Work with product managers, data engineers, software developers, and domain experts to deliver AI capabilities.
• Document solutions, create technical guides, and support adoption of AI features.

Required Skills & Qualifications

• Bachelors or Masters degree in

  Computer Science, AI/ML, Data Science, or related field

  .
• Strong proficiency in

  Python

  and ML libraries (TensorFlow, PyTorch, Hugging Face Transformers).
• Hands-on experience with:
• Large Language Models (GPT, LLaMA, Claude, etc.)
• Fine-tuning and prompt engineering
• Vector databases (FAISS, Pinecone, ChromaDB)
• Model deployment (Docker, Kubernetes, FastAPI, Azure/AWS/GCP)
• Understanding of NLP, deep learning, neural network architectures.
• Experience with

  MLOps tools

  (MLflow, Weights & Biases) is a plus.
• Knowledge of

  Responsible AI principles

  , safety frameworks, and data privacy.