Techspert are looking for a keen and enthusiastic engineer to join our Research Engineering team. The successful candidate will work with other Research Engineers, Data Engineers and end users to identify and build new ways to improve the search system that powers our expert network.
Expert networks are a nascent but rapidly growing service: the best way to make a difference in our rich and complex world is to have a conversation with an expert! Connecting those experts with the people they can help is key to this. Scaling our business requires automated tools that accurately and efficiently predict the suitability of an expert for a given client project, based on a variety of public, volunteered and inferred information.
We are seeking a candidate that has a passion for applying machine learning techniques to real business problems, and building deployable models and algorithms using evidence-based criteria.
We are keen to see applications from experienced generalists as well as deep specialists, and from Data Scientists or Machine Learning Engineers who want to focus on robustly building and evaluating applied models.
** This role can be 100% remote, but candidates must be located within the EU or UK**
You will need an interest in applying existing technology to business problems. You will also need to have a mix of software engineering and research experience. Any experience in natural language processing (NLP), ontologies and sematic web, or information retrieval systems will be a benefit.
Successful applicants will also need to work effectively with a mixed hybrid and remote team and support the team in embedding good software practices.
This is a hands-on role investigating and developing improvements for internal systems. Your time will be spent:
Accountable to the Product team for designing and delivering experiments that evaluate candidate technologies and approaches, and providing recommendations and next steps.
Accountable to the Data Engineering team for building models that can be deployed to production without re-engineering.
Accountable to the Research Engineering Lead for supporting the growth and development of the team, as well as maintaining good software engineering standards.