Geospatial AI Engineer / Applied Scientist

Full Description

Job Title

Geospatial AI Engineer / Applied Scientist

Location

London

Right to work in the UK required (visa sponsorship considered on a case-by-case basis)

Time Commitment & Working Arrangement

This is a full-time position (40 hours per week).

The role requires focused, dedicated commitment to Nyxium.

• External paid work, consulting, or freelance engagements outside Nyxium are not permitted during employment.

• Any academic affiliations, advisory roles, or unpaid activities must be disclosed and must not conflict with Nyxium’s work, priorities, or intellectual property.

• We value sustainable working practices and do not expect routine overtime, but we do expect full professional focus during agreed working hours.

About Nyxium

Nyxium is a London-based deep tech company backed by top-tier investors.

We are building an agentic AI and geospatial intelligence platform that supports siting, permitting, impact assessment, and decision-making for complex infrastructure projects, including energy systems, data centers, and other critical infrastructure.

Role Summary

We are seeking an Applied Scientist with deep expertise in geospatial analytics, machine learning, and large-scale data systems to design, build, and productionize advanced analytical and AI-driven solutions.

This role sits at the intersection of spatial science, ML engineering, and applied research, and requires hands-on ownership of end-to-end pipelines, from data ingestion and modeling to deployment and stakeholder delivery.

The ideal candidate is comfortable working across remote sensing, spatial statistics, deep learning, graph models, NLP, and cloud-native ML infrastructure, and can operate both as a senior individual contributor and a technical mentor.

You will be expected to ship and make architectural decisions.

Key Responsibilities

Geospatial & Spatial Analytics

• Lead development of geospatial data products using satellite imagery, LiDAR, SAR, hyperspectral data, and derived indices (NDVI, NDSI, night-light metrics, greenspace/blue-space indicators).

• Perform advanced spatial analysis, including spatial autocorrelation, clustering, multilevel modeling, dimensionality reduction, and geospatial time-series analysis.

• Build graph-based spatial models and image-based feature extraction pipelines using PyTorch and related frameworks.

• Develop and maintain high-quality geospatial databases with strong attention to data governance and privacy.

Machine Learning & AI

• Support NLP or LLM-based workflows when spatial and text data intersect.

Design, develop, and productionize machine learning and deep learning models, including classification, regression, time-series, survival analysis, and anomaly detection models.

• Build and optimize deep learning architectures such as CNNs, U-Nets, LSTMs, GNNs (GCN), and transformer-based LLM workflows.

• Develop Retrieval-Augmented Generation (RAG) and LLM-based pipelines for data imputation, NLP analysis, and decision support.

• Apply Bayesian and frequentist statistical methods, including hierarchical, spatiotemporal, and latent structure models, to generate robust, interpretable results.

Data Engineering & Production Systems

• Build scalable pipelines using Python, SQL, Spark, and cloud-native tools.

• Work with BigQuery, Postgres/PostGIS, MongoDB, and distributed storage systems to support analytical and ML workloads.

• Orchestrate pipelines using tools such as Apache Airflow, and support real-time and batch analytics.

• Collaborate on production deployments across AWS and/or GCP, including Vertex AI and large-scale ML infrastructure.

Collaboration & Ownership

• Work directly with founders on technical direction and roadmap execution.

• Translate real-world problems into robust technical solutions.

· Own and evolve Nyxium’s geospatial intelligence layer, including spatial schemas, constraint logic, and site-scoring methodologies.

· Design explainable and auditable geospatial outputs suitable for high-stakes decision-making and regulatory review.

Product, Stakeholder & Research Collaboration

• Work closely with product managers, engineers, and stakeholders to translate real-world problems into technical solutions and roadmaps.

• Support A/B testing, cohort studies, and experimental design to evaluate impact and outcomes.

• Mentor junior data scientists and engineers on spatial analytics, ML best practices, and statistical reasoning.

• Contribute to internal research, documentation, and where appropriate, external publications.

Required Qualifications

Education

• PhD or Master’s degree in Spatial Sciences, Geospatial Engineering, Data Science, Computer Science, Statistics, Environmental Science, or a closely related field.

Core Technical Skills

• Programming: Python (advanced), SQL; working knowledge of R and JavaScript.

• Machine Learning: Regression, Random Forest, GBM, SVM, clustering, deep learning, GNNs, LLMs (GPT/BERT).

• Geospatial Stack: GeoPandas, GDAL, rasterio, Shapely, Fiona, xarray, QGIS/ArcGIS, Google Earth Engine.

• Remote Sensing: Optical, SAR, LiDAR, hyperspectral data; image segmentation and feature extraction.

• Statistics: Bayesian hierarchical models, spatiotemporal modeling, survival analysis, multivariate analysis.

• Big Data & Cloud: Spark, BigQuery, AWS, GCP, Vertex AI, HDFS, Airflow.

• Databases: Postgres/PostGIS, BigQuery, MySQL, MongoDB.

Experience

• 5+ years of professional experience in data science, applied ML, or geospatial analytics, including production systems.

• Demonstrated experience delivering end-to-end ML solutions in complex, real-world environments.

• Experience working with large, messy, multi-source datasets, including spatial and text data.

Preferred / Nice-to-Have

• Experience in health, infrastructure, environmental, or urban analytics domains.

• Experience with fraud detection, anomaly detection, or risk modeling.

• Experience building internal tools, dashboards, or ML-powered decision systems.

• Track record of peer-reviewed publications or applied research contributions.

What Success Looks Like

• You independently ship production-ready ML and geospatial systems that stakeholders trust.

• You raise the technical bar for spatial analytics and applied AI within the organization.

• You balance scientific rigor with practical delivery and timelines.

• You act as a force multiplier by mentoring others and improving system architecture.

Compensation

Salary

• We offer competitive and above market salary and meaningful equity.

• Final offer depends on experience and scope of responsibility.

Benefits

• Flexible, remote-first working arrangement

• Pension contributions (UK auto-enrolment)

• Paid annual leave and UK public holidays

• Direct access to founders and real influence over technical direction

• Opportunity to work on high-impact, technically challenging problems from the ground up

Why Join Us

• You will work on core systems, not peripheral features.

• Your work will directly shape the product and company trajectory.

• You will join at a stage where ownership, trust, and technical judgment matter.

• You will not be buried under layers of management or unclear priorities.

How to Apply

Please send your CV and a short note explaining your interest in Nyxium and your experience with geospatial or spatial-ML systems to hr@nyxium.ai.

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