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Director of Machine Learning

Harnham
London
1 month ago
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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.

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