Description

You will design and implement state-of-the-art generative AI solutions and end-to-end pipelines for enterprise use cases.

Responsibilities

• Develop and implement AI models using Large Language Models (LLMs) and generative AI techniques.
• Integrate APIs and libraries including Azure OpenAI GPT models and Hugging Face Transformers.
• Build and optimize end-to-end pipelines for data processing and model deployment.
• Manage large-scale datasets using vector databases like Redis and NoSQL databases.
• Implement similarity search algorithms to enable accurate information retrieval.
• Conduct research into transfer learning, domain adaptation, and model compression to improve efficiency.
• Establish evaluation metrics to assess the quality, coherence, and relevance of AI outputs.
• Ensure all applications comply with data privacy, security, and ethical standards.

Required Skills

• Minimum 4 years of experience in Data Science and Machine Learning.
• Proficiency in Python and R.
• Deep understanding of Machine Learning, Deep Learning, and Generative AI.
• Experience with NLP frameworks including BERT, GPT, or Transformer models.
• Hands-on experience with TensorFlow or PyTorch.
• Experience deploying AI solutions on Azure, AWS, or GCP.
• Strong data engineering skills for curating, cleaning, and preprocessing large-scale datasets.
• Knowledge of MLOps, DevOps, and AI solution architecture.
• Familiarity with computer vision techniques such as image recognition or object detection.

Preferred Skills

• Experience designing AI systems within the security or cybersecurity domain.
• Knowledge of trusted AI practices regarding fairness, transparency, and accountability.

Key Skills

Education

Any Graduate