Machine Learning Software Developer/Engineer (KTP Associate)

Employer: University of Hertfordshire
Job location
Hitchin and Hatfield
Job salary
30,942 - 33,797
Job term
Job closing date

Heales’ vision is to provide world class cost effective OH services, minimising absence & maximising staff wellbeing and driving this vision through innovative technology. The successful development of an Artificial Intelligent (AI) diagnostic & recommendation platform will dramatically reduce the cost of services, help resolve the labour shortage in trained nurses and provide an ever-improving service to clients.

The company’s key strategic aims are:

• To accommodate and serve the small/medium employer market in OH services, benefitting more employees in society in an area overlooked by much of the industry. The automated, intelligent platform offers significant cost reduction in resources used in health assessments and a streamlined recommendation report process, enabling SMEs to both financially access the services and be better able to manage OH requirements for their staff.
• To start delivering services globally, starting with increased service offering across the UK. This will result in hiring more staff in regional areas, increasing job opportunities outside major cities.
• As a technological first mover in OH, Heales will expand their reputation as an innovation leader in the industry.


The KTP Associate will be responsible for delivering the KTP work plan, described below:

Stage 1 – Company and use-case understanding: The Associate will acquire an understanding of the processes, magnitude of the challenge, and the commercial significance of automation question
generation (AQG) and opinion mining (OM).

Stage 2 – Definition of the Problem: Acquire an understanding of components of assessments, and Natural Language Processing (NLP). Undertake a review of AQG & OM literature to inform the approach. Workflow pattern & question report, report state of the art automation, structure requirements, and system/user requirements

Stage 3 - Data Acquisition: Perform machine learning training and write deep learning algorithms, introduction to NLP technology. Ensure data is stored and labelled for databases and deep learning systems to produce a report of OH use-cases. Create a database on language structure.

Stage 4 - Solving the Problem: Perform steps necessary to develop a prototype, evaluate it, then design the module and interface functionality necessary to integrate the module into the company’s existing software.

Stage 5 - Module Build Integration and Testing: Solution implementation including referencing historical data from use-case, evaluation and refinement of integrated system. After the module has been developed and integrated, provide a software integration and testing report, followed by a performance report once the improved version has gone live.

Stage 6: Field Trial: Implementation of AQG and OM for assessing the credibility of the system in a live setting. Provision of user training and interpretation of the system. Produce a specification and plan, deliver, roll out, and then report on the analysed data, produce spec. for system refinements, and make the upgraded system live.

Stage 7: Business Development/Commercialisation: Marketing, promoting AQG & OM capability to new clients and scope post-KTP spin-out options. Marketing strategy recommendations, update to system functionality to meet client requirements; perform client-led updates, devise strategy for post-KTP exploitation, undertake SWOT analysis, draft contract terms proposal, Knowledge Transfer presentation, E-discover and compliance monitoring.

Stage 8: Embedding and Disseminating the Knowledge: Deployment of AQG & OM modules. New functionality adopted by company. Produce final spec document, produce full program code doc. Migration of final program code, production of SOP & user guides, SOP for system maintenance; draft academic publications & conference papers, deliver a seminar on AQG from text, Knowledge Transfer presentation, final doc updates, demo of new functionality, staff handover, final seminar to review project to company management.


The Associate will be employed by the University of Hertfordshire on a 24-month contract but will also carry out duties at Heales’ company site in Hitchin, and at the University of Hertfordshire at Hatfield, depending on which aspect of the project is being worked on at the time.

Expert supervision will be provided by the School of Engineering and Computer Science. The Associate will report to and be managed by their University line manager, who will also be their Academic Supervisor at the University, who will provide support and help with technology, tools and techniques.

The Associate will also have a Company Supervisor at Heales to provide direction of commercial activities and day to day duties. Project meetings will be held on a monthly basis and chaired by the Associate, where both the Academic Supervisor (Line Manager) and Company Supervisor will attend. High level programme review ‘Local Management Committee’ (LMC) meetings will be held every 4 months where the Associate will provide a formal presentation on progress. Further expert supervision will be provided by the School of Engineering and Computer Science as required.

Hours of work at Heales Ltd are: 9:00am to 5:00 Monday to Friday totalling 37.5 hours per week excluding a 30 minute lunch break per day.
Holiday: 22 days per year excluding bank holidays; pro-rata in the first year according to start date.

The Associate will also be allocated 10% of their time supported by a £4,000 budget for the purpose of technical, professional and personal development.
Information contact details: Helen Podmore, tel: 01707 286406 email:

This document outlines the main duties required for the post entitled Machine Learning Software Developer / Engineer to indicate the level of responsibility. It is not intended to be a comprehensive or inclusive list and duties may vary, though will not change the general character of the job or the level of responsibility entailed.