Senior Applied AI Scientist

Direct message the job poster from Deep Rec.ai

Location: UK-based, remote-first (with monthly optional meetups in London)
Start date: ASAP
Eligibility: Must have the right to work in the UK

Deep Rec.ai has the pleasure of partnering with a remote-first NbS startup as they look to hire a Senior Applied AI Scientist to lead the development of ML-driven solutions that scientifically quantify the real-world impact of nature-based interventions. You'll join a multidisciplinary team of AI scientists, engineers, and environmental experts tackling one of the biggest challenges of our time: building trusted, scalable tools for climate and biodiversity action.

• Shared purpose, no ego.
• Remote-first with flexible working hours, built on trust.
• Monthly team meetups at a London-based office (Highbury).
• Clear communication, fast iteration, and support over silos.
• A culture that thrives on ambiguity, feedback, and a growth mindset.

• Design, build, and scale machine learning models using environmental and observational data.
• Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods.
• Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets.
• Work cross-functionally with science, engineering, and product teams to embed models into real-world pipelines.
• Communicate scientific and technical concepts clearly to both technical and non-technical audiences.
• Stay current with the latest developments in AI and environmental science, integrating relevant innovations into production.
• Mentor junior team members and foster best practices in applied ML.

• Strong background in applied machine learning, bayesian statistics, and causal inference.
• Proficiency in Python and ML frameworks such as PyTorch.
• Experience with cloud infrastructure (e.g., AWS, GCP).
• A clear, concise communication style - clear examples given when asked, not word salad.
• An adaptive mindset and comfort working in fast-changing environments.
• A deep motivation to contribute to climate and ecological impact.
• An advanced degree (MSc or PhD) in Computer Science, Statistics, Economics, Physics, Mathematics, or a related field.

• Experience working with geospatial or spatial-temporal data.
• Experience with remote sensing datasets (e.g., Landsat, Sentinel, SAR).
• Familiarity with Torch Geo or Terra Torch.
• Experience with Rasterio, Geopandas, Xarray, or Dask.
• Previous collaboration with academic or scientific research communities.
• Publications in peer-reviewed journals or conferences.

• Remote-first and flexible hours
• 32 days paid holiday (including bank holidays, fully flexible)
• Extra day off on your birthday
• Pension scheme
• Enhanced gender-neutral parental leave
• Spill mental wellbeing support
• Company laptop + home working setup allowance

• Not Applicable

• Full-time

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