Senior Applied AI Scientist
Location: UK-based, remote-first (with monthly optional meetups in London)
Start date: ASAP
Eligibility: Must have the right to work in the UK
Overview
DeepRec.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.
The Culture
* 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.
What You’ll Do
* 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.
What You Bring
* 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.
Nice to Have
* Experience working with geospatial or spatial-temporal data.
* Experience with remote sensing datasets (e.g., Landsat, Sentinel, SAR).
* Familiarity with TorchGeo or TerraTorch.
* Experience with Rasterio, Geopandas, Xarray, or Dask.
* Previous collaboration with academic or scientific research communities.
* Publications in peer-reviewed journals or conferences.
Benefits
* 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