AI Engineer / Artificial IntelligenceContract- Banking

AI Engineer (Banking/Fintech Exposure Preferred)Roles & Responsibilities:- Develop intelligent solutions using Agentic frameworks, Large Language Models (LLMs), and Model Context Protocol (MCP) to deliver fast and scalable services across the organisation.- Collaborate closely with software and data science teams to understand requirements and design appropriate solutions.- Deploy and productionise machine learning (ML) and generative AI (GenAI) models on company infrastructure.- Maintain and manage existing AI models, including monitoring for data drifts and hallucinations as part of MLOps responsibilities.- Contribute to and conduct research on AI frameworks and AI-safety evaluations of domain-trained models.- Stay up to date with the latest developments in AI and introduce AI/GenAI solutions to enhance existing processes, serving as an AI subject matter expert.Requirements:- Bachelor’s degree in computer science, computer engineering, data science, or a similar field, or equivalent experience/certifications.- Minimum of 2 years’ experience in deploying and productionising large language models (LLMs).- Experience with fine-tuning or domain adaptation of LLMs is a plus.- Proficiency in programming languages such as Python.- Experience working with retrieval augmented generation (RAG) processes.- Familiarity with frameworks such as scikit-learn, PyTorch, LangChain, or other machine learning/agent frameworks.- Experience with platforms such as Hugging Face, MLFlow, or similar.- Proficiency with Docker or other containerization platforms.- Experience with shell scripting and working in a Linux environment. EA Reg. No. 25C2690 | EA License No. R1877766

AI Engineer (Banking/Fintech Exposure Preferred)

Roles & Responsibilities:
- Develop intelligent solutions using Agentic frameworks, Large Language Models (LLMs), and Model Context Protocol (MCP) to deliver fast and scalable services across the organisation.
- Collaborate closely with software and data science teams to understand requirements and design appropriate solutions.
- Deploy and productionise machine learning (ML) and generative AI (GenAI) models on company infrastructure.
- Maintain and manage existing AI models, including monitoring for data drifts and hallucinations as part of MLOps responsibilities.
- Contribute to and conduct research on AI frameworks and AI-safety evaluations of domain-trained models.
- Stay up to date with the latest developments in AI and introduce AI/GenAI solutions to enhance existing processes, serving as an AI subject matter expert.

Requirements:
- Bachelor’s degree in computer science, computer engineering, data science, or a similar field, or equivalent experience/certifications.
- Minimum of 2 years’ experience in deploying and productionising large language models (LLMs).
- Experience with fine-tuning or domain adaptation of LLMs is a plus.
- Proficiency in programming languages such as Python.
- Experience working with retrieval augmented generation (RAG) processes.
- Familiarity with frameworks such as scikit-learn, PyTorch, LangChain, or other machine learning/agent frameworks.
- Experience with platforms such as Hugging Face, MLFlow, or similar.
- Proficiency with Docker or other containerization platforms.
- Experience with shell scripting and working in a Linux environment.

EA Reg. No. 25C2690 | EA License No. R1877766