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Opal Platform Engineering

Roles & Responsibilities

  • Hands-on experience with at least one major TMS (XTM, Phrase, memoQ, Trados)
  • Strong understanding of XLIFF/MXLIFF formats and translation pipelines
  • Experience using Python (or AI-assisted coding tools) to build scripts for data processing
  • Basic SQL proficiency (writing, generating, and validating queries)

Requirements:

  • Configure and maintain platform environments across TMS platforms, including MT engine connections and workflows.
  • Act as the primary diagnostics layer between production teams and AI/ML Engineering, investigating MT quality issues and escalating with clear reproduction steps.
  • Manage end-to-end MT operations: data preparation, TM analysis, engine training, evaluation, deployment, and monitoring.
  • Support pre-sales as an MT/AI subject matter expert, build ROI models, prepare QBR insights, and advise clients on MT strategy.

Job description

About Welo Global 

Welo Global is a leader in multilingual AI, technology, and content solutions serving over 2,000 clients in 300 languages. The company combines globally scaled multilingual infrastructure, including a network of over 500,000 linguists and domain experts, with advanced NLP, computational linguistics, and best-in-class compliance backed by seven ISO certifications. Welo Global’s five brands—Welocalize (multilingual content and localization services for global enterprises), Park IP (intellectual property and patent translation services for law firms and corporate legal teams), Welo Life Sciences (regulated language and compliance-aligned content solutions for pharmaceutical, biotech, and medical device organizations), Adapt (multilingual performance-led digital marketing agency), and Welo Data (multilingual data generation, evaluation, and human data infrastructure for AI systems)—serve distinct customer segments with purpose-built expertise, fit-for-purpose solutions, and supporting technology. weloglobal.com  


ROLE OVERVIEW

This role sits at the operational core of our internal platform, Opal, ensuring clients are configured, operational, and supported without requiring direct AI/ML Engineering involvement for routine matters.

The ideal candidate is a technical operator with a strong problem-solving mindset, capable of bridging client delivery and platform mechanics. You should be comfortable troubleshooting a broken MT pipeline, presenting performance data in a QBR, and building lightweight automation to eliminate manual work—all within the same week.

 MAIN RESPONSIBILITIES 

  • Configure and maintain platform environments across TMS platforms (e.g., XTM, Phrase, memoQ, Trados), including MT engine connections, workflows, AIPE/AIQE parameters, and provider-level settings (glossaries, dictionaries, model selection).
  • Act as the primary diagnostics layer between production teams and AI/ML Engineering. Investigate MT quality issues, identify root causes (data, engine, pipeline, or TMS), and escalate with clear reproduction steps and context.
  • Manage end-to-end MT operations: data preparation, TM analysis, engine training, evaluation, deployment, and monitoring. Maintain relationships with MT providers and identify opportunities to optimise performance.
  • Support pre-sales as an MT/AI subject matter expert. Build ROI models, prepare QBR insights (e.g., edit distance trends, MT savings, cost usage), and advise clients on MT strategy, including engine selection and content suitability.
  • Identify and eliminate manual processes through automation. Design or build tools, scripts, and workflows that reduce human intervention and improve scalability. This is a core expectation of the role.
TECHNICAL SKILLS & REQUIREMENTS 
 
Core Technical Skills 
  • Hands-on experience with at least one major TMS (XTM, Phrase, memoQ, Trados), including configuration of MT integrations, workflows, and templates
  • Strong understanding of XLIFF/MXLIFF formats and translation pipelines
  • Experience integrating MT providers (e.g., Google AutoML, Microsoft Custom Translator, DeepL, Systran)
  • Knowledge of MT customisation, including training data, model types (generic vs custom NMT), and quality drivers
  • Familiarity with MT evaluation metrics (BLEU, TER, edit distance) and human evaluation frameworks
  • Understanding of the MT lifecycle: preprocessing, training, evaluation, deployment, and monitoring
  • Ability to navigate provider platforms and understand their capabilities, limitations, and pricing models
Technical Experience
  • Experience using Python (or AI-assisted coding tools) to build scripts for data processing (e.g., cleaning TMX files)
  • Strong data manipulation skills (e.g., Pandas or equivalent via AI-assisted workflows)
  • Basic SQL proficiency (writing, generating, and validating queries)
  • Experience building lightweight tools or internal apps (e.g., dashboards, file processors)
  • API integration experience: reading documentation, generating code, testing, and debugging
  • Comfortable working in terminal/command-line environments
  • Ability to read and validate code, including AI-generated scripts
  • Strong understanding of data workflows (input → transformation → output)

Data & Reporting

  • Excel / Google Sheets (including pivot tables)
  • Power BI or similar reporting tools
  • Familiarity with structured data formats: CSV, JSON, XML, TMX
Other Skills 
  • Python (advanced)
  • LLM / prompt engineering experience
  • Annotation tools (e.g., Label Studio)
  • Cloud platforms (GCP, Azure, AWS)
  • Jira or similar project management tools
  • Localization industry knowledge (translation workflows, post-editing, quality frameworks, LSP operations)
COMPETENCIES
  • Bias for action: Prioritises speed and execution over perfection
  • Automation mindset: Constantly identifies opportunities to remove manual work
  • Ownership: Works independently and makes decisions with incomplete information
  • Commercial awareness: Understands how MT impacts revenue, cost, and client value
  • Problem-solving orientation: Focuses on outcomes, not tools
We prioritise problem-solving ability using modern tools, including AI-assisted development (e.g., Cursor, Claude Code, Copilot), over memorisation of syntax.
 
This role is not about traditional engineering. It is about using AI and modern tools to solve operational problems quickly and effectively, and knowing when the solution is correct.

 

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