Principal Data Scientist (AI Model R&D)

In this role, you will:Lead a complex suite of interacting projects; either technical complexity and interdependency, or business/stakeholder interactions. Play a key leadership role that has far reaching impact throughout the whole team – through formal reporting lines or technical and/or project leadership, you will drive the culture and technical vision for the team.Take a very high level of personal responsibility and accountability for projects, capabilities, etc. within the team. Key skills & experience we are looking for:Extensive relevant experience, ideally 10+ years in research or industry, resulting in a powerful combination of intuition, pragmatism, theoretical understanding, and impeccable judgment.Experience with large-scale model training systems or other high-performance computing.Programming/Tech Environments: Ability to code in scientific Python and experience working on shared codebases to produce production-quality code.Machine Learning and AI: Strong grasp of machine learning fundamentals (regularization, hyperparameter optimization, validation methods) and recent AI advancements. Experience with machine learning applied to image data is highly desirable.Cloud Computing: Experience working on AWS or GCP using distributed virtual machines, Docker containers, etc.Scale: Experience working with large datasets that don't fit into memory and require multiple nodes for efficient computation.Scientific Approach: Follow the scientific method of formulating hypotheses and applying statistical tests to validate them.Pragmatism: While extensive knowledge of ML theory is highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.Collaboration: We believe data science is a team sport, and are after candidates who can communicate well, share knowledge, and be open to taking on ideas from anyone in the team. Having worked on shared code-bases in a commercial environment is a big plus, but it's the attitude that matters most.Attention to detail: Showing attention to detail when it counts is important.