Director of Machine Learning & AI

London – Hybrid (3 days in office)

Up to £125,000 + Equity

About the Role

A fast-scaling climate tech company backed by investors is looking for a Director of AI & ML to lead the development of advanced machine learning solutions that help global banks, insurers, and real estate firms understand and act on physical climate risk. You’ll define the ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting.

Key Responsibilities

• Own and evolve the company’s AI & ML strategy in line with product and customer priorities
• Lead, mentor, and grow a high-performing team of ML Engineers
• Take prototypes through to production, delivering meaningful product features powered by GenAI and predictive modelling
• Collaborate with Science and Engineering to integrate ML with physics-based climate models
• Communicate complex technical concepts in simple, outcome-oriented terms for customers and cross-functional teams

Your work will focus on delivering high-value insights and solutions, including:

• Developing generative AI tools for geospatial risk assessment
• Building models to project the impact of floods, cyclones, heat stress etc
• Leveraging satellite imagery and remote sensing for climate hazard detection
• Enhancing time-series forecasts to inform asset-level risk planning
• Combining simulation outputs with ML for hybrid physical + statistical modelling

What We’re Looking For

• Proven leadership and strong hands on experience
• Proven track record of deploying ML into production environments
• Depth in at least one of: generative AI, geospatial ML, computer vision, or forecasting
• Experience working with climate data (or similar)
• Excellent communication skills and cross-functional collaboration ability
• Experiene working in start ups/ scale ups.

Bonus Points

• Experience with satellite imagery or other Earth-observation data
• Exposure to climate risk, catastrophe modelling, or environmental data
• Familiarity with physics-informed ML or simulation-driven techniques
• Background in regulated or data-sensitive industries

If this role looks of interest, please apply below.