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.
- Work closely with the 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 on company infrastructure, 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.
- Maintain knowledge of regulatory standards for AI, particularly in the context of the financial services industry.
Requirements
- Bachelor's degree in computer science, computer engineering, data science, or a similar field, or equivalent experience/certifications.
- At least 2 years of 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. R1330510
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