Research Scientist

Darwin Geospatial is looking for an AI Engineer / Applied AI Scientist

We are seeking a research-driven AI Engineer with deep mathematical training and strong applied modeling experience to join our team in Madrid.

Our work sits at the intersection of applied research, scientific computing, and production engineering, turning mathematical ideas and models into systems that operate at real-world scale.

This role is particularly well suited for candidates transitioning from academia (maths, engineering, physics, etc..) This position is intended for senior profiles with PhD-level training and a strong research background.

AI & Modeling:

PyTorch, custom neural architectures, optimization algorithms, loss design, uncertainty estimation •

Mathematics & Foundations:

linear algebra, probability theory, statistics, numerical optimization, information theory •

Geospatial & Remote Sensing:

Infrastructure & Cloud:

Docker, Google Cloud (Cloud Build, Vertex AI, Cloud Run, Cloud SQL) •

Backend & APIs:

FastAPI, REST API design, authentication, modular system architectures •

Experimentation:

MLflow, reproducible research pipelines, model versioning •

Testing & Reliability:

pytest, CI pipelines, model validation strategies •

Python, numpy, pandas, matplotlib

PhD (or equivalent research experience) in applied mathematics, physics, computer science, AI, or a closely related field • Demonstrated research experience (peer-reviewed publications, preprints, or equivalent industrial research output) • Experience leading model development from research prototype to deployed system • Prior work in geospatial AI, remote sensing, Earth observation, or spatiotemporal modeling • Contributions to open-source scientific or ML software • Experience collaborating with academic institutions or research consortia • Familiarity with additional compute environments (AWS, Azure, HPC clusters) • Experience mentoring or supervising junior engineers or researchers

Competitive compensation aligned with senior research and engineering roles, adapted to an early-stage startup environment • High technical autonomy and ownership over model design, research direction, and system architecture • A strong research culture with the explicit goal of publishing applied research in peer-reviewed venues and top-tier conferences, when appropriate • Close collaboration with senior engineers, applied scientists, and external research partners • Long-term incentive alignment through the possibility of equity participation with a vesting schedule, based on performance and mutual commitment • Flexible schedule and hybrid work model (Madrid), with a strong focus on outcomes rather than hours

This is a Hybrid position based in Madrid