reinforcement learning, and supervised fine-tuning (SFT). Model Deployment & Inferencing : Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-AgentSystems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on … fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js) and API development. Familiarity with vector search and multi-agent orchestration Apply now to join this high growth and award-winning organisation with the opportunity to be part of building the future of AI driven More ❯
closely with data engineers, researchers, and platform teams to ensure robust deployment.Continuously research and integrate emerging techniques in agent-based AI, multi-agentsystems, and reinforcement learning.Required Skills & Experience:4+ years of experience in AI/ML engineering or data-intensive systems.Strong proficiency in Python for AI … libraries such as TensorFlow, PyTorch, LangChain, or Ray is a plus.Ability to write clean, efficient, and well-documented code in a collaborative environment.Desirable:Experience with multi-agent coordination or LLM-based autonomous agents.Background in distributed systems, knowledge graphs, or real-time data processing.Contributions to open-source AI projects or relevant research More ❯
Assess the practicality and relevance of modern technologies such as machine learning, big data analytics, generative AI, multi-agentsystems, and quantum computing in insurance and risk consulting. Work with diverse teams to pinpoint challenges in the industry and devise innovative solutions using these technologies. Examine intricate data sets to offer More ❯
