Deep Learning Specialist

At Treefera we build AI-native data systems that bring clarity and credibility to nature-based assets — enabling organisations to make and defend high-impact decisions about risk, resilience and commercial performance. You’ll join a global, cross-functional team that values rigour, curiosity and working close to real-world challenges. Whether your focus is AI, climate, product or operations, you’ll have space to contribute meaningfully and make an impact from day one. If you’re excited by complex problems and want to help reshape how nature is valued in real-world decision-making, we’d love to hear from you.

Must-have requirements:

• Strong background in Machine Learning, Deep Learning, and Applied Statistics.
• Experience with time-series modelling. Familiarity with building and backtesting.
• Proficiency with the Python scientific stack: scikit-learn, PyTorch, scipy etc.
• Familiarity with version-controlled, reproducible workflows (AWS/cloud infrastructure, Git, WeightsBiases/experiment tracking).

Desirable requirements (if applicable):

• Experience with risk modelling, financial time series and portfolio optimisation techniques.
• Experience working with weather and climate data, particularly CMIP archives and weather forecast data.
• Experience with geospatial techniques (rasterio, xarray, geopandas, GDAL) and remote sensing data (optical, radar, LiDAR) is beneficial.
• Familiarity with MLOps practices (containerisation, CI/CD, model monitoring) is a plus.
• Prior experience in a startup or fast-moving product team.

What the job involves:

• As a key member of the AI team, you will design, implement, and evaluate ML/DL models for processing alternative data sources (satellites and weather data) for risk and trading signals.
• Forecasting environmental or risk-related signals (e.g. increasing weather and climate volatility, agricultural stress indicators).
• Use remote sensing datasets (e.g. Sentinel-1, Sentinel-2, GEDI, other optical and radar missions) and climate data to build vegetation stress signals, landcover classifications and land-surface conditions.
• Develop time-series and forecasting models to detect and anticipate environmental changes and their impacts on global markets.
• Collaborate closely with the wider AI, Science, Product, and Engineering teams to translate business questions into robust modelling problems.
• Turn research prototypes into scalable, reliable AI pipelines that deliver actionable information.
• Help shape modelling standards, documentation, and reproducibility within the AI team (e.g. experiment design, evaluation protocols, uncertainty treatment).
• Communicate methods, assumptions, and results clearly to technical and non-technical stakeholders, including limitations and uncertainty.

What you’ll gain at Treefera:

• Build a high-growth climate-tech company from the ground up.
• Apply AI and data to global, nature-based challenges that matter.
• Work on real-world systems balancing risk, resilience, compliance and sustainability.
• Collaborate with a diverse, cross-functional, global team.
• Access competitive pay, equity and meaningful benefits.
• Help shape the future of AI-powered risk and environmental data analysis, building systems that give organisations an information advantage.

Diversity, Equity & Inclusion:

Bold solutions come from diverse teams. Please refer to our DEI & EEO commitment below. If you need any accommodation during the application process, we’re here to support you.

By applying to Treefera, you consent to the processing of your personal data in line with our Privacy Notice. Treefera is an equal opportunity employer. We believe the diversity of our people is as vital as the diversity of the ecosystems we work to protect, and we are committed to building an inclusive workplace where everyone can thrive. We welcome applicants of all backgrounds irrespective of race, colour, ethnicity, national origin, religion, gender identity or expression, sexual orientation, age, disability, pregnancy, or any other characteristic protected by applicable law. Reasonable accommodations are available upon request.