Spatial AI and Machine Learning Consultant

NFP PEOPLE; Remote; GBP 60,000 - 80,000; Part time

Job summary

A leading environmental charity is seeking a Freelance Spatial AI and Machine Learning Consultant to shape and deliver innovative geospatial products. This role involves strategic and technical leadership in developing AI systems that address key environmental challenges. The ideal candidate has at least five years of experience in AI, spatial data science, and strong familiarity with UK datasets. This is a remote position based in the UK, offering up to 24 days of consultancy throughout the year.

Qualifications

• Minimum 5 years' experience in AI and machine learning.
• Strong proficiency in spatial data science.
• Ability to identify risks and propose mitigation.

Responsibilities

• Lead technical direction of AI/ML products.
• Advise on model selection and deployment strategies.
• Mentor internal staff on predictive and spatial modelling.

Skills

AI, predictive analytics and machine learning model development

Spatial data science and GIS (QGIS, ArcGIS Pro, Python GIS)

PyTorch and Ultralytics YOLO

Cloud data management (AWS or Azure)

Working with UK socio-environmental datasets

Job description

Overview

Freelance Spatial AI and Machine Learning Consultant — Contract: February – December 2026. Days: Up to 24 days total (typically 1–2 days per week, with higher demand in the first quarter). Location: Remote, UK-based. Rate: Self employed day rate aligned with equivalent annual salary.

A national environmental charity is seeking an experienced Freelance Spatial AI and Machine Learning Consultant to help shape and deliver two innovative geospatial digital products. These tools one a predictive risk model, the other a computer vision system for detecting and classifying litter will play a key role in improving public spaces, reducing waste, and supporting future data integration.

This is a unique opportunity to lead the strategic and technical development of cutting edge AI/ML systems that will have real world environmental impact.

Key Responsibilities

Strategic & Technical Leadership

• Review project objectives and shape the technical direction of both AI/ML products.

• Advise on model selection, training, testing and deployment strategies.

• Provide recommendations that consider scalability, licensing, futureproofing and cost effectiveness.

• Contribute to final recommendations on how the enhanced frameworks can support national scale litter prevention and resource targeting.

Risk Model Review & Enhancement

• Evaluate the existing geospatial modelling pipeline, including architecture, data inputs, feature engineering and algorithm performance.

• Recommend improvements to workflows, feature sets and geospatial techniques.

• Support experimentation using predictive modelling approaches such as Random Forest and Gradient Boosting.

• Strengthen validation processes, including training/testing design, diagnostics and error analysis.

• Conduct independent quality assurance to assess robustness, stability and interpretability.

Computer Vision System Development

• Define the vision, success criteria and performance targets for a new litter detection computer vision model.

• Develop a data acquisition and annotation strategy with strong QA processes.

• Evaluate alternative model families, annotation schemas and deployment architectures.

• Validate the end to end development plan, ensuring alignment with scope, timeline and complexity.

• Design evaluation and error analysis frameworks to measure real world performance and guide iteration.

• Advise on long term sustainability, technical debt reduction and modular upgrade pathways.

Stakeholder & Project Management

• Manage milestones, dependencies and deliverables, keeping internal stakeholders aligned.

• Communicate technical concepts clearly to non technical audiences.

• Provide written technical notes and participate in short progress meetings.

Capacity Building & Documentation

• Mentor internal staff on advanced predictive and spatial modelling methods.

• Review and contribute to clear, auditable technical documentation.

Person Specification

Essential

• Minimum 5 years’ professional experience in AI, predictive analytics and machine learning model development.

• Strong proficiency in spatial data science and GIS enabled modelling (QGIS, ArcGIS Pro or Python GIS stack).

• Skilled in PyTorch, Ultralytics YOLO and cloud data management (AWS or Azure).

• Experience working with UK socio environmental datasets (IMD, ONS, land use, accessibility).

• Experience integrating models into offline or on prem environments.

• Ability to identify risks early and propose practical mitigation strategies.

• Proven experience maintaining stakeholder alignment across project milestones.

• Right to work in the UK, ability to demonstrate contractor status, and professional indemnity insurance.

Desirable

• Experience in environmental risk modelling, urban analytics or behavioural data analysis.

• Understanding of geostatistics, spatial interpolation and postcode level disaggregation.

• Familiarity with environmental behaviour change programmes.

If you’re excited by the opportunity to shape impactful AI systems that support cleaner, greener communities, we’d love to hear from you.

For more information, please contact Hannah at NFP People.