At the start of this week, I attended an event organised for in-house translators by Universitas. I was part of a small and eclectic group, meeting at the end of the working day. From a very interesting and relaxed couple of hours talking with the others in the group a number of things sprung to mine, which I addressed the following day on LinkedIn.
- There is no “one-size-fits-all” in-house role. Expectations on in-house translators vary dramatically: from subject matter specialists through to multi-language pair generalists. There is no hard and fast rule about work in a single language pair or multiple pairs. Even classical “Translator” positions may involve a mixture of translation and other activities. For applicants for such positions, it is advisable at interview to ask about the likely expected hours dedicated to translation.
- Job descriptions for open vacancies are seldom as straightforward as “Translator (m/f/d)”. Translation is frequently only a part of the job description, and the job title is seldom for only a translator. In language career portals in the German-speaking world (e.g. Stepstone, Kununu or Karriere.at) most hits for the skill “Übersetzung” talk about it figuratively.
For example a recent job advert for Österreichische Post AG for an Expert in Controlling Insights mentioned “Du fungierst als “Dolmetscher” zwischen Fachbereich und Programmierer und bist zuständig für die Übersetzung der Anforderungen des Fachbereichs in detaillierte Vorgaben und Zielsetzungen für technische Umsetzung.” In other words – nothing to do with translation or interpreting! In other cases it might be disguised in a job description for a “zweisprachige Schreibkraft” or “Kommunikationstalent”. This latter role is closer to transcreation than translation. Here are some common language-based job titles. - The burgeoning TechStack: among the group around the table, the tools used, and expectations regarding such tool use was varied. There were also varying views about the expectations regarding the use of GenAI/LLMs. Some are very open to the possibilities, while others actively decline to use such tools, or are not permitted to do so.
Often required training regarding GenAI/LLMs is not specifically tailored to translators. Similarly, the effective use of such tools for translators is not as clear cut as the hype makes out. Deployment of new tools is often IT-led. This approach sometimes overlooks those with genuine expertise to really use them and assess the quality of their output.
Resource issues
- Double-hatting is common: some translators also work as interpreters, rather than having separate translation and interpreting personnel. Others in-housers are only part-time in-house, so have to juggle self-employment alongside their fixed employment.
This naturally places additional demands on them in terms of time management and also how to organise their time effectively. Teleworking may have cut out some unnecessary miles/kilometers, but there is still a lot of juggling required with multiple positions. - Working for a demanding customer base with dwindling human translation capacity: this can become even more difficult if language services are overseen by non-linguists. This can make it more difficult to discuss the need for quality that goes beyond “good enough”, and where “fit for purpose” is a minimum requirement.
It can be difficult to get past only being viewed as a cost centre. Translation can be quantified easily in terms of cost, but its impact on sales etc. is more difficult to quantify. Tighter budgets mean fewer retiring colleagues are replaced, or FTEs are replaced by fractional headcount. Alternatively FTEs might only have a certain percentage of their time devoted to translation. - Decreased job security: even in public administration there are perceptions that the job security of translators is lower than it used to be. The erosion of the classical triple constraint, the rise of “good enough”, and the improved “linguistic fitness” of many white collar colleagues has affected demand for translators.
Job mobility and exchange programmes while studying mean that many colleagues are more confident in their language abilities that only a few years ago. However, there is still a subjective basis to their assessment of their own language abilities. Just as having two hands and a piano does not make me a concert pianist, working knowledge of two languages, does not automatically transfer into being able to write well in your target language. - Rising expectations in terms of output: while tools like CAT and (N)MT have helped to increase translator productivity, there is still the unrealistic expectation in light of the promises of “instant translation” offered by browser-based tools.
Translators’ potential output can really depend on so many factors – NMT/GenAI/LLMs are “confidently wrong” – they will always offer a translation, whereas the “cautiously correct” human translator reverts to the author if unsure – to clear up potential source or target text ambiguities.
Similarly, expectations vary wildly based on the percentage of time spent on translation compared to non-translation activities. Often there is no dedicated capacity for terminology work. Only larger language units have dedicated terminologists: without them, it is often widely neglected. With the advent of MT/GenAI and the Terminology Augmented Generation approach, which is used to import your terminology into the LLM, it is likely to gain in importance.
Are you interested in events like this? Universitas holds regular events throughout the year. Check out the Universitas website for more information – if you are not yet a member, some events are open to guests. If you are interested in knowing more about what I do, then why not join the Universitas Berufsbilder webinar on 23 October 2025, which will focus on the role of project management and process management.
