EXPERT COURSE

Machine Translation and Automated Post-Editing MTQE-APE

Master Automated Quality Control for Scalable MT Workflows

As AI-driven translation becomes the backbone of modern localization pipelines, organizations urgently need reliable, automated quality mechanisms to reduce linguistic risk while maximizing cost efficiency.
Today, over 82% of global enterprises already use MT in their content operations, and more than 70% rank quality assurance as their top challenge when scaling MT outputs (CSA Research, “Enterprise Machine Translation Adoption”, 2023).

Core Operational Knowledge

This specialized course distills the core operational knowledge behind MT Quality Estimation (MTQE) and Automated Post-Editing (APE), two technologies crucial to achieving no-touch translation, minimizing human intervention, and ensuring predictable quality across high-volume workflows.


Participants will learn how hybrid MT systems—combining NMT engines with LLM-based components—use scoring, confidence estimation, and automated linguistic corrections to build robust quality gates, monitor MT performance, and automatically repair content before it reaches human linguists or end-users.


Conditions: Please read our course and subscription plans terms and conditions carefully. With your registration, you confirm that you have read, understood and accepted our conditions and agree with them. 

If you have any questions, please visit the FAQ section (for courses or subscription plans) or get in touch with us.

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  • This course includes:
  • Expert coach:
    Andrés Romero Arcas, Language Technology Expert at Acolad
  •  Interactive activities
  •  Life access to contents 
  •  In English
  •  Completion certificate
  •  Money back guarantee
  • Acquire A-Z knowledge about AI Translation
  • When: 09-10 February 2026 - 18.00 CET
  • Duration: 4 h approx.

Course and Instructor Description

Machine Translation Quality Estimation and Automated Post-Editing (MTQE–APE) is your fast-track guide to building hands-free, scalable, AI-powered translation workflows.

In just 4 intensive hours, you’ll learn how leading organizations use MTQE scoring and automated post-editing to cut review costs, boost quality consistency, and unlock true “no-touch” translation at scale.

Through real-world examples and a live hands-on lab using OpenAI Agent Builder, you'll discover how to implement smart quality gates, automate linguistic corrections, and blend NMT with LLMs to create next-generation hybrid MT systems.

Perfect for anyone who wants to increase automation, reduce human dependency, and elevate operational efficiency across their localization pipeline.

Instructor: Andrés Romero Arcas
Andrés Romero Arcas is an AI and Language Technology Specialist with strong experience in NMT, LLMs, MTQE, and automated translation workflows. He focuses on practical, scalable AI solutions for localization teams and is known for explaining complex technology in a clear, actionable way.
Session 1: Hybrid Workflow: MTQE & APE
Session 2: Hands-on Practice: Building MTQE-APE with OpenAI Agent Builder
Session 1

Hybrid Workflow:
MTQE & APE

Session 1. Hybrid Workflow: MTQE & APE

1.1 Why hybrid workflows outperform traditional MT pipelines
1.2 MTQE + APE standard workflow
1.3 Quality estimation models and scoring
1.4 Automated post-editing mechanisms
1.5 Integrating human linguists into the workflow
1.6 Quality monitoring and management
1.7 Strategic best practices
Session 2

Hands-on Practice: Building MTQE-APE with OpenAI Agent Builder

Session 2. Hands-on Practice: Building MTQE-APE with OpenAI Agent Builder

2.1 Overview of Agent Builder architecture
2.2 Working with Agents, Variables, Set State, and If/Else
2.3 Designing logic for quality estimation and automatic post-editing
2.4 Building your own automated workflow simulation
Meet

Andrés Romero

Andrés is a proficient language technology expert with over a decade of experience in the Localization Industry.
Throughout his career, he has held diverse roles, such as CAT Tool Specialist, Localization Engineer and Operations Technology Coordinator, where he led a team of localization engineers.
Currently at Acolad, Andrés focuses on machine translation evaluation and engine training. He is also deeply involved in prompt engineering and Generative AI, proposing AI-driven driven solutions to deliver tailored, customer-centric solutions and to tackle challenges in Production.
Andrés is passionate about automating and optimizing processes to enhance productivity and efficiency, improving quality and integrating innovation into localization workflows.
Andrés Romero - Course Creator & Host
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