Associate Staff Engineer, Generative -AI

Job description

REQUIREMENTS:

• Total Experience 5+years.
• Deep understanding of Generative AI fundamentals and transformer-based architectures.
• Deep understanding of Natural Language Processing (NLP) and experience with models like GPT, BERT, T5, etc.
• Strong working experience in Python and key ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Hands-on experience with prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques.
• Experience deploying models on cloud platforms such as AWS, GCP, or Azure, and knowledge of MLOps best practices.
• Collaborate with product managers, data scientists, and engineering teams to deliver AI-powered solutions.
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML pipelines.
• Strong analytical, problem-solving, and communication skills.

RESPONSIBILITIES:

• Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the client's requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.