Our world is currently going through the most significant period of globalization in human history. Although English is still a second language for many around the world, most people still feel more comfortable in their own native language or in the language that they know best.
At the same time, more and more people are talking about the exploding volume of multilingual content sitting on the web and on the servers of international corporations and smaller companies. A significant chunk of this content has a certain value, but in many cases it is not considered important enough to hire professionals to translate it.
The emergence of Machine Translation (MT) technology has made it possible to have these documents available in multiple languages. Sometimes the quality of translation can be relatively low, but without MT, this content would never been translated at all.
Another attractive characteristic of MT is that it enables an increase in the productivity of translators without reducing the quality of translation. In this instance, translators are presented with the output of the MT engine (aka Google Translate) and are asked to simply post-edit the MT output instead of translating from scratch. For most languages, this is faster and demands far fewer resources.
These are only two of the reasons why MT is emerging as one of the most important technologies in the modern industrial world.
MT is constantly improving. It is a hot industry, with millions of strategic and technical challenges to be solved. A professional or a recent graduate with experience and/or background in MT has a lot of opportunities in the worldwide job market.
Let’s have a look at the types of companies who are often interested in hiring MT professionals:
- Machine translation service providers. Big and small IT companies that provide their own MT solutions or customize off-the-shelf and commercial MT engines. Jobseekers can look to take this path if they are strong at research and are fast and efficient at implementing new features to the MT engine. Examples: Google (Google Translate R&D group), Microsoft (Microsoft Bing R&D group), Asia Online (customization of O/S Moses engine), Systran (the oldest players on the market), ProMT (Hybrid MT).
- International corporates adopting MT technology and localization departments and R&D labs of big companies. Recently, corporates that view multilingualism as a strategic issue have started adopting existing MT systems or developing their own MT solutions. They need MT specialists to partially or totally automate the translation process. This category of companies also includes public international organizations, like Patent Offices.Examples: Autodesk, eBay, AT&T, World and European Patent Offices.
- Language Service Providers (LSPs). Currently LSPs, who represent a significant percentage of MT buyers, are in different phases of MT implementation and customer-oriented adoption. For their goals, I would expect a high level of correlation between MT and translation memory technology. Examples: HP ACG, SDL, Semantix.
- Academia: universities and research centers. In academia, MT is considered one of tasks of artificial intelligence research and a sub-domain of computational linguistics. MT has become an extremely popular and intensively funded research area. Over the last few years MT has been intensively funded by European Commission, the US and Canadian governments through a number of short- and mid-term projects. Jobseekers interested in pursuing an academic career, including those who want to complete a PhD, can try to find a position within one of these projects or joining permanent University staff.Examples: Institutions active in MT research: Carnegie Mellon University, University of Edinburgh, RWTH – Aachen University, Projects: Moses Core, EXPERT, FAUST
- Government labs and research centers. MT is a strategic goal for at the governmental level too. MT systems for this type of use traditionally incorporate MT solutions from different providers (commercial and open-source). Since the majority of the MT-related research for government applications is concentrated in USA, the eligibility criteria often includes US citizenship and security clearance.Examples: National Institute of Standards and Technology, Language Technologies Research Centre, MIT Lincoln Lab.
We’ve been collecting a number of statistics since our launch in May 2012. Let’s have a look at some that are applicable to MT:
Table 1. Distribution of MT-related jobs per type of hiring institution.
|Type of company||Number of job ads|
Of all the jobs advertised at nlppeople.com, more than half are submitted by corporates, international institutions and academia. A low level of hiring at LSPs indicates that translation agencies are not convinced enough about MT to run the risk of developing their own MT solutions.
Table 2. Distribution of MT-related jobs per country.
|Country||Number of jobs|
Almost half of the jobs are concentrated in the USA, followed by the European localization hot-spot of Ireland and the Benelux countries. The UK’s market share is a bit lower for the MT market than for the NLP market in general (6.25 % versus an overall share of 10.21 %).
Table 3. Distribution of MT-related jobs per type of employment.
|Type of employment||Number of jobs|
The lion’s share of jobs in industry are full-time, permanent positions, while in academia practically all the openings are fixed term jobs. Freelancing – a popular option for many IT people seeking to earn a flexible income – hardly features as a possibility in the MT market at the moment.
MT is booming. MT’s time has come. The number of companies and academic institutions hiring people with an MT background is increasing, so don’t lose your chance to jump in!
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