My Perspective on Localization Engineering

My Perspective on Localization Engineering

2025, May 27    

Interview with Nicholas Lambson: The Localization Engineer Profile

The below interview was conducted by Marco Pirrone, a student of mine through Localization Summer School. I have enhanced it with AI after the interview to more comprehensively reflect my perspective.

Role of Localization Engineer within Application Software and Game Industries

Marco Pirrone: Can you briefly describe the role of Localization Engineer professional profile within application software and game industries?

Nicholas Lambson:
A localization engineer facilitates the technical aspects of a localization project, ensuring the smooth adaptation of websites, apps, software, and video games for international audiences. A localization engineer typically works on either the client side—localization buyers or language service buyers (LSBs)—or the vendor side—localization providers or language service providers (LSPs). My experience is exclusively from the vendor side, providing localization services for a range of different clients, whether for video games, apps, websites, or software. The main responsibility is to bridge the gap between development and translation, ensuring technical processes and file types are handled in a way that is compatible both with engineering and with linguists’ needs.

Required Technical and Soft Skills

Marco Pirrone: In your opinion, what kinds of technical and communicative skills should be possessed by Localization Engineers, especially in order to act as bridgers profiles between programmers and localizers?

Nicholas Lambson:
We can divide localization engineer skills into two broad categories: technical (hard) and communicative (soft) skills. It’s essential for localization engineers to be able to act as a bridge between programmers and linguists, so both sets of skills are critical.

Technical (Hard) Skills

  • Content Types:
    Engineers should be adept at managing a variety of content types and file formats, such as:
    • Microsoft Office: Word, Excel, PowerPoint
    • Adobe publishing tools: InDesign, Illustrator, FrameMaker
    • Technical documentation systems: MadCap Flare, DITA
    • Android/iOS strings
    • JSON, Java .properties files
    • Web formats: HTML, CSS, JavaScript, XML/XHTML
    • Game development: Unity, Godot, ClickTeam Fusion
    • Video and subtitle files (.srt)
    • Fonts, encoding, and internationalisation best practices
    • Localization industry formats: XLIFF, TMX, TBX
  • Tools and Systems:
    • CAT tools: memoQ, SDL Trados Studio
    • TMS: WorldServer, XTM, Memsource (Phrase)
    • Other tools: Passolo, ApSIC Xbench, Okapi Rainbow, Okapi Checkmate, BeyondCompare, BulkRenameUtility, UTFCast
    • MT and AI tools: Google Cloud, Intento, OpenAI
    • Enterprise systems: Microsoft SharePoint, XTRF, Plunet
  • Scripting and Automation:
    • Proficiency in Python for automation, text manipulation, and custom tool creation
    • Regular expressions
    • IDEs: Visual Studio Code
    • Version control using Git/GitHub
    • Command line and scripting (e.g., VBA in Office)
    • Connecting via APIs

Soft Skills

  • Work Estimation & Project Planning: Accurately estimate effort, including best- and worst-case scenarios.
  • Technical Communication: Explain technical concepts to non-technical audiences and educate both clients and team members about technical issues or best practices.
  • Collaboration: Ability to request help from co-workers or freelancers and communicate with teammates from various backgrounds.
  • Data Analysis: Analyze and present data clearly and convincingly, such as translation progress, cost, and quality.
  • Process Documentation: Thoroughly document code and processes in internal knowledge bases (e.g., SharePoint, MediaWiki) for continuity and handover.
  • Issue Tracking & QC: Track progress of multi-language/multi-file projects, troubleshoot issues, and run QA scripts/macros.
  • Ownership: Take responsibility for mistakes, implement immediate fixes, and put long-term guardrails in place using approaches like Root Cause Analysis and Corrective Action Reports, especially in ISO-certified environments.
  • Linguistic & Orthographic Awareness: Recognize all languages and script codes and understand where/how particular languages and scripts are used (e.g., Simplified vs. Traditional Chinese, Mandarin vs. Cantonese, orthographic differences like Cyrillic, decimal separators, spaces).
  • Cultural & Linguistic Sensitivity: Understand the orthographic, cultural, and practical differences in international projects.

Tools and Operating Procedures

Marco Pirrone: Can you mention some reference support tools and operative approaches which can be useful during localization engineering tasks?

Nicholas Lambson:
My top advice is to learn Python, as it’s the most versatile scripting language for automation, file transformation, and custom tooling. Alongside that, it’s critical to become proficient with leading CAT tools like SDL Trados Studio and memoQ, as well as tools such as Okapi Rainbow and Checkmate for processing and QA. BeyondCompare is excellent for source/target file comparisons. Regular expressions are also invaluable for quick pattern-based edits.

Also, familiarize yourself with:

  • File Preparation Approaches:
    • Source file analysis, text extraction, filtering, segmentation, pseudotranslation, workflow design, asset setup, MT/AI setup, word count, TM leverage, project/task aggregation.
  • Engineering QA/Post-Production:
    • Encoding and font checks, HTML entities, line endings, CSV delimiters, escaped characters, catching untranslated strings, terminology, numbers, placeholders, orthography, compiling, running scripts/macros for QA, and using BeyondCompare for final checks.
  • Automation:
    • Scripting in Python, regex, using VS Code, connecting data/process through APIs for scalable automation.
  • Documentation:
    • Clear documentation of code and process in Markdown, using screenshots, following UI style guides (e.g., Microsoft), storing in SharePoint/MediaWiki.
  • Business Operations:
    • Using business management systems, email, to-do lists, calendars, reports (Word/Google Docs), and dashboards/data visualizations (Excel/Sheets).

Prompt engineering, especially for leveraging AI in task automation or QA, is another high-value skill as you advance in localization engineering.

Open Challenges in the Field

Marco Pirrone: Can you briefly describe some of the main open challenges in this field?

Nicholas Lambson:
There are several persistent challenges:

  • Contextual Awareness:
    Translators need as much context as possible to ensure quality. Unfortunately, the standard workflow often strips content of its context (often presenting strings in a two-column table). Some TMS platforms offer workarounds, like showing screenshots or HTML previews, but it remains a common pain point—especially for narrative-heavy media like games.
  • Machine Translation (MT) and AI Integration:
    Integrating MT and AI into localization workflows is both exciting and hard. Training and deploying custom MT engines with well-prepared data—using platforms like Intento or Custom.MT—and applying advanced AI (such as quality estimation, automatic post-editing, multimodal localization, synthetic data generation) requires deep expertise. Evaluating MT quality might involve BLEU, GEMBA, and similar metrics.
  • Source File Management:
    Often, clients provide content in suboptimal formats (e.g., PDF), which can make engineering and localization tedious. It’s much more efficient to receive editable source files. Text embedded in images or vector art is also a persistent challenge.
  • Content Variety & Learning Curve:
    The diversity of project and content types—including all the various structured documentation formats, games, websites, etc.—demands a steep learning curve. Mastering universally-used formats like DITA can set engineers apart, but it’s a big commitment.
  • Automation & Documentation Gaps:
    Not all engineers have strong programming (automation) or technical writing (documentation) skills, yet these skills create the most value. Efficient engineers automate repetitive tasks, clearly document the rest, and outsource where possible.
  • Continuous Learning & Adaptation:
    New tools, formats, and standards are continually emerging. Keeping up is a career-long effort and a source of both excitement and challenge.

Standard Framework and Entry Requirements

Marco Pirrone: How would you suggest to create a standard framework for this professional profile? What kinds of degrees and/or other entry requirements would you consider?

Nicholas Lambson:
Localization engineering is a hybrid discipline, requiring mostly technical skills but also linguistic and cultural savvy. Localization engineers work on both the client and vendor sides, and typically have one of two educational backgrounds:

  1. Technical Background
    (Computer Science, Software Engineering, IT, Information Systems, Data Science)
    These engineers are ready for the technical localization tasks but may lack experience with language or internationalization. They often start on the client side as developers, later transitioning into localization or i18n roles.

  2. Language Background
    (Foreign Languages, Translation Studies, Linguistics)
    These engineers often supplement their education with coursework or projects in programming, corpus analytics, data science, NLP, or computational linguistics. They often start on the vendor side and must ramp up on technical skills.

No single degree program fully prepares someone for the full localization engineer role. You must be proactive: research the profession, build your own course plan, and ensure both skill sets are represented. Here’s how I’d design an ideal framework:

  • Curriculum Focus: About 80% technical skills and 20% linguistic and cultural awareness.
  • Balanced Experience: Vendor-side engineers often start with language and add technical skills; client-side engineers usually have technical backgrounds and must learn localization-specific concepts like internationalization and translation technology.

Suitable Degrees

  • Computer Science / Software Engineering / Information Technology / Information Systems / Data Science
  • Foreign Languages / Translation Studies / Linguistics

Suggested University Program & Courses

If you can choose or supplement your academic plan, aim for courses such as:

  • Computer-assisted translation tools (CAT)
  • Advanced business applications (Microsoft Office Suite)
  • Introduction to localization
  • Python programming (ideally spanning four semesters)
  • Database management
  • Technical writing
  • Business communications
  • Data science
  • Information systems
  • Web development
  • Software/mobile development
  • Machine Translation: history and practice
  • Prompt engineering
  • Natural Language Processing (NLP)
  • Linguistics and translation theory
  • Localization engineering (using Python, recommended as a two-semester sequence)

My Perspective on Programming

I believe programming skills—especially Python—are absolutely critical. When I started, I didn’t know Python, but I quickly grasped its value in automating localization tasks and developing custom tools. A big thanks to my supervisor, who encouraged me to continue learning. Over the years, I’ve become an expert, earning the PCPP (Python Institute) certification and even developing my own training course, “Python for Localization,” which distills over a decade of industry experience.

The Python Institute provides accessible certification programs:

Additionally, actively participate in industry forums, conferences, and continuous training. The diversity of the field means you’ll keep learning on the job, but a strong, purposefully selected academic foundation puts you ahead.

In summary:
The profile of a localization engineer is multi-faceted: you have to be a flexible technologist, capable communicator, and lifelong learner, with an ability to blend language awareness and technical precision. The best localization engineers are those who automate processes, share knowledge, and create bridges—not just between systems, but between teams and visions. If you are committed to developing both your programming and your linguistic/cultural sensitivities, you’ll thrive in this unique and evolving field.

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# education # localization # ai