Artificial Intelligence/Machine Learning Engineer

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying scalable AI/ML models, including Generative AI applications. Your role will involve leading end-to-end data science projects, from data collection and preprocessing to modelling and evaluation. You will collaborate with cross-functional teams to integrate models into production systems, ensuring optimal performance and robustness across diverse datasets. Additionally, you will conduct research to stay updated on the latest advancements in AI/ML and Gen AI. Your key responsibilities will include: - Training and fine-tuning LLMs using domain-specific data to enhance performance in specialised contexts - Utilizing LVM, Agentic AI, tool handling, function handling, MCP, and Multimodal RAG in different domains - Developing techniques to scale LLMs efficiently for high-volume production environments - Designing and implementing novel approaches to model optimisation and evaluation - Collaborating with cross-functional teams to integrate AI solutions into production systems - Keeping current with the latest research and incorporating state-of-the-art techniques - Documenting methodologies, experiments, and findings for both technical and non-technical audiences As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying scalable AI/ML models, including Generative AI applications. Your role will involve leading end-to-end data science projects, from data collection and preprocessing to modelling and evaluation. You will collaborate with cross-functional teams to integrate models into production systems, ensuring optimal performance and robustness across diverse datasets. Additionally, you will conduct research to stay updated on the latest advancements in AI/ML and Gen AI. Your key responsibilities will include: - Training and fine-tuning LLMs using domain-specific data to enhance performance in specialised contexts - Utilizing LVM, Agentic AI, tool handling, function handling, MCP, and Multimodal RAG in different domains - Developing techniques to scale LLMs efficiently for high-volume production environments - Designing and implementing novel approaches to model optimisation and evaluation - Collaborating with cross-functional teams to integrate AI solutions into production systems - Keeping current with the latest research and incorporating state-of-the-art techniques - Documenting methodologies, experiments, and findings for both technical and non-technical audiences