Full-Time

Localization Lead

Engineering & Automation

Apertera

Apertera

1-10 employees

SaaS translation platform with human post-editing

No salary listed

Toronto, ON, Canada

Hybrid

Hybrid work is available in Toronto or Montreal.

Category
Engineering Management (1)
Required Skills
LLM
Airflow
Data Visualization
HubSpot
Data Engineering
RAG
Quality Assurance (QA)
JIRA
n8n
REST APIs
DevOps
Data Analysis

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Requirements
  • Hands-on experience in automation, workflow orchestration, internal tooling, or data engineering, including scripting, working with application programming interfaces, connecting disparate systems, and building reliable operational workflows.
  • Direct experience in the language technology ecosystem, such as a computer-assisted translation or translation management system environment, a machine translation or language artificial intelligence platform, or a technical role within a language service provider involving translation workflows.
  • Strong understanding of translation memory leverage, fuzzy matching, and terminology management, with the judgment to set direction, prioritize linguistic-asset quality work, and be accountable for measurable gains.
  • Working knowledge of professional translation workflows, including intake, project setup, pre-translation, machine translation post-editing, revision, quality assurance, delivery, and production reporting.
  • Practical experience designing, improving, or operating integrations between systems, including application programming interface design, integration patterns, data flow, and monitoring.
  • Experience leading or managing a technical or cross-functional team, such as engineering, automation, solutions engineering, localization engineering, data, analytics, or internal tooling.
  • Ability to work directly with operational teams, understand real production workflows, distinguish quick wins from deeper structural work, and deliver solutions adopted in practice.
Responsibilities
  • Own and prioritize the Professional Translation workflow automation and internal tooling roadmap, ensuring initiatives are practical, scalable, and tied to clear operational outcomes.
  • Identify and deliver automation across the production lifecycle, including intake and quoting, file analysis, project setup, assignment logic, vendor and resource workflows, quality-assurance tracking, and production reporting.
  • Build and operationalize automation and workflow orchestration across Professional Translation, connecting production systems into reliable, auditable workflows that reduce manual effort and meet client confidentiality and security requirements.
  • Treat translation memories, terminology, and related linguistic assets as core productivity and quality assets.
  • Drive improvements in translation-memory leverage, fuzzy-match optimization, terminology consistency, and reuse, especially in high-repetition financial, legal, and securities content.
  • Direct specialist work related to maintaining, segmenting, improving, and measuring the performance of linguistic assets.
  • Use operational data across Plunet, Phrase, HubSpot, Jira, ATAI, finance, quality assurance ticketing, and other tools to improve visibility, decision-making, and measurable impact.
  • Improve data flow and integration across core production systems to reduce duplicate entry, strengthen operational visibility, and support consistent handoffs.
  • Partner with the broader Technology organization on architecture, security, and shared infrastructure so Professional Translation tooling fits the company’s wider technical environment.
  • Help establish and manage a small agile team focused on localization engineering, automation, linguistic data, analytics, and workflow tooling.
  • Establish delivery cadence, quality standards, and adoption practices for tooling used in a high-precision translation environment.
  • Work with Linguistic Operations leadership to identify workflow gaps, quality risks, and automation opportunities and translate them into technical requirements and delivery plans.
  • Ensure solutions are designed for adoption by project managers, quoting, resources, linguists, revisors, desktop publishing, quality assurance, and finance teams.
  • Define and track success metrics tied to reduced manual work, improved translation-memory and terminology leverage, stronger quality-assurance visibility, faster turnaround, better consistency, and operational scalability.
  • Identify internal workflow improvements, automation solutions, quality-assurance tools, integrations, or operational innovations with broader productization potential for Apertera AI clients.
Desired Qualifications
  • Working familiarity with machine translation, large-language-model-based translation, or retrieval-augmented generation for integration and orchestration decisions.
  • Exposure to quality estimation, adaptive machine translation, or orchestrating large-language-model or retrieval-augmented-generation components within production workflows.
  • Familiarity with DevOps practices, continuous integration and continuous delivery, infrastructure as code, dashboards, data pipelines, or localization engineering.
  • Experience in regulated industries such as legal, financial, securities, or government, where accuracy, confidentiality, and data sovereignty are critical.
  • Background in localization engineering, computational linguistics, natural language processing, language technology product development, or technical product or program management.
  • Experience in a high-growth or scale-up environment building processes alongside products.
  • Bilingual or multilingual proficiency.

Apertera provides Enhanced Machine Translation through a proprietary SAAS called Yappn Technology System (YTS) that localizes websites, customer care, and social media posts into 100+ languages. The system combines advanced machine translation with human post-editing to deliver more accurate and contextually correct translations. It integrates with client platforms, enabling implementation in a few weeks via existing integration points. Compared to typical MT offerings, Apertera emphasizes higher-quality translations and a post-edited workflow, helping clients grow by reaching new markets and better serving customers who prefer languages other than English. The company's goal is to help businesses communicate, conduct commerce, and engage socially across language barriers.

Company Size

1-10

Company Stage

IPO

Headquarters

New York City, New York

Founded

2013

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Simplify Jobs

Simplify's Take

What believers are saying

  • June 2026 launch positions Apertera for broader enterprise AI sales beyond translation.
  • It claims over 75% of major Canadian law firms, creating strong reference leverage.
  • ISO 17100 and SOC 2 certifications support regulated procurement and faster security approvals.

What critics are saying

  • Apertera remains narrowly exposed to Canadian translation workflows and regulated content budgets.
  • Enterprise buyers can shift to Microsoft, DeepL, or internal LLM tools within 12 months.
  • Branding overhang from the 2026 rename can confuse customers and dilute search demand.

What makes Apertera unique

  • June 2026 rebrand from Alexa Translations signals regulated-workflow AI beyond generic translation.
  • Apertera targets legal, financial, and regulatory buyers, including major Canadian banks and securities regulators.
  • Its Adaptive AI and client-context training fit high-stakes documents requiring precision and consistency.

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Benefits

Hybrid Work Options

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