Description

You will architect and build large-scale, production-grade Generative AI systems.

Responsibilities

• Design and implement scalable, performant, and secure AI system architectures.
• Develop and deploy ML/DL models, specifically leveraging LLMs and RAG approaches using open-source models.
• Engineer solutions involving Vector Databases and Graph Databases for efficient information retrieval.
• Build and validate commercial-grade software within high-availability service contexts using agile practices.
• Collaborate with cross-functional teams, including data scientists and delivery engineers, to define and meet requirements.

Required Skills

• 11+ years of professional experience building complex software systems.
• Minimum 3 years hands-on experience in AI/ML/Deep Learning projects.
• Proficiency in Python and ML libraries such as TensorFlow and PyTorch.
• Deep understanding of Transformer and Diffusion models (e.g., BERT, GPT, Stable Diffusion).
• Experience with cloud platforms (AWS SageMaker, Azure OpenAI, GCP Vertex AI, or IBM WatsonX).
• Practical experience tuning and deploying models, including hyperparameter optimization and evaluation metrics (F1 score, accuracy).
• Working knowledge of Distributed Systems and modern Cloud Technologies.
• Experience with programming languages including Python, C, C++, C#, or Java.
• Familiarity with LangChain frameworks and prompt engineering techniques.

Key Skills

Education

Any Gradute