Senior Machine Learning Scientist (Agentic Modelling Team)

Join as a Senior Machine Learning Scientist in the Agentic Modeling Team. You will research, design, and develop core AI capabilities for our agentic platform, focusing on agent strategies, reasoning architectures, context management, memory systems, and multi-agent patterns. Collaborate with cross-functional teams and ensure research translates into production-grade capabilities. Enjoy a range of benefits including health insurance, paid time off, and discounts on our products. - Research, design, and develop core AI capabilities for the agentic platform, focusing on agent strategies, reasoning architectures, context management, memory systems, and multi-agent patterns. - Collaborate closely with ML engineers to ensure research translates into production-grade capabilities with appropriate latency and reliability, and build reusable ML components that encode production best practices. - Lead the development of advanced agent strategies, context management, and multi-agent patterns, and help build systematic experimentation and optimization backed by quantitative analysis. - Successfully driving technical and people-related initiatives while communicating with stakeholders at all levels - Experience designing and building production agentic or conversational AI systems at scale - Relevant work or academic experience (MSc + 6 years, or PhD + 4 years), applying Machine Learning to business problems - Leading by example, developing your team and motivating them to achieve their goals. Providing timely feedback and managing key performance indicators - Experience designing and executing end-to-end R&D plans. Preferably evidenced by peer-reviewed publications, patents, or open-source contributions - Excellent English communication skills, both written and verbal - Experience collaborating cross-functionally in the development of ML-powered products - Strong working knowledge of Python and ML/AI frameworks. Experience with LLM APIs and retrieval systems - Experience with LLM evaluation and optimization - designing metrics and systematically improving model-based systems - Masters degree, PhD or equivalent experience in a quantitative field (e.g., Computer Science, Artificial Intelligence, Mathematics, Physics, etc.) - Advanced knowledge and experience in NLP, LLM-based systems, and agentic AI architectures - including tool use, reasoning, retrieval-augmented generation, and agent planning