Technology Specialist (Data & AI)

The UK Agri-Tech Centre

3d•Hybrid

About The Position

Provide specialist data engineering, AI/ML and analytics expertise to support ventures developing autonomous or automated agricultural systems. This includes field robotics, mechatronic systems, airborne platforms (e.g., UAVs), and automation workflows across horticulture and field settings. Ensures data-led technologies are integrated, validated and evidenced appropriately across trials, working collaboratively across TTD, and ensuring interoperability, standards and data quality throughout delivery. Undertake horizon scanning to ensure that new data/AI technologies, companies and opportunities are identified and evaluated. Team Purpose: Shape the organisations’ data & AI roadmap and ensure technical expertise informs SME progression, facility development and programme delivery. Enabling ventures to validate performance, generate trusted operational data, and accelerate commercial adoption of robotics solutions. This is a hybrid role based at our tech site at Cranfield. Travel to other sites might be required occasionally.

Requirements

Postgraduate qualifications in a relevant discipline.
Proven experience of ETL/ELT and data automation (e.g. FME Flow/Form, Python); strong geospatial skills (e.g. PostGIS).
Working understanding of ML/computer-vision data pipelines, labelling and annotation requirements and data-quality processes for AI.
Excellent communication and interpersonal skills, with the ability to engage and influence a diverse range of stakeholders.
Experience of diagnosing and resolving data engineering issues (schema design, validation, performance, integration).
Experience in delivering workshops and presentations.
Strong analytical and problem-solving skills, with a focus on innovative and practical solutions.
Strong organisational skills and the ability to prioritise tasks effectively when multi-tasking.
Good teamwork, using a collaborative approach and excellent consultative skills.
Ability to deliver accurately to tight deadlines and under own initiative.
Ability to translate technical information for non-technical audiences.

Nice To Haves

Understanding of the R&D process, the agri-tech sector, and agricultural datasets/sector geospatial sources.
Familiarity with MLOps/DataOps and ML training pipelines.
Exposure to on-prem/hybrid environments (e.g. Hyper-V) and Linux administration.
A successful history of applying for grant funding and commercial tenders.
Familiarity with national/international agricultural data‑standards initiatives and interoperability schemes.
Excellent IT skills and proficient with Microsoft environments, including task management tools.
Full UK driving licence.

Responsibilities

Support technology businesses with their data/AI development and commercial value propositions, aligning with sector and commercial realities and linking them to relevant expertise.
Provide insight to define data strategies and evidence plans for trials (capture, metadata, quality, benchmarking), working collaboratively with the Trials and Facilities teams.
Maintain and grow specialist and sector knowledge, staying at the forefront of developments in the UK and internationally and utilising this knowledge to set strategic direction, support technology businesses and create partnerships.
Technical leadership: Advise businesses on ETL/ELT, data models, geospatial workflows and AI readiness, and lead technical aspects of product development in programme and project work where data is core.
Stakeholder engagement: Demonstrate sector leadership in engaging across the agri-tech ecosystem, building and maintaining strong relationships with key stakeholders and contributing to national data standards and interoperability discussions.
Data analysis: Understand, interpret and present technical data to generate clear, defensible insight for ventures and to support the development of data/AI technologies.
Horizon scanning: Identify new technologies and businesses to engage with, supporting the development of new strategy and/or business opportunities.
Design and review data flows for trials, to ensure benchmark-ready datasets are created for businesses.
Build or guide pipelines (e.g. FME Flow/Form, Python-based automation) and geospatial data processes (e.g. PostGIS) where needed; diagnose schema, performance and integration issues.
Work across the wider TT&D team to enhance our capabilities and identify new opportunities.
Contribute to evidence frameworks (benchmarking, inputs to TEA/LCA) and to e.g. AI data labelling and computer-vision workflows.
Deliver/contribute expertise to commercial and CR&D projects as required.
Support the delivery of technical events such as technology demonstrations in an engaging and professional manner.
Sector leadership function with respect to data & AI