Full-Time
Localization Engineering Manager
Apertera
1-10 employees
SaaS translation platform with human post-editing
No salary listed
Montreal, QC, Canada
Hybrid
Hybrid work model with a mix of in-office collaboration and remote flexibility.
Category
 Engineering Management (1) |
|---|
Required Skills
LLM
Airflow
HubSpot
Data Engineering
Infrastructure as Code (IaC)
RAG
Quality Assurance (QA)
n8n
REST APIs
DevOps
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Requirements
- Experience leading or managing a technical team, including hiring, mentoring, and delivery ownership.
- Hands-on background in automation, workflow orchestration, and data engineering, including building and operating pipelines with tools such as n8n and Apache Airflow, scripting, working with application programming interfaces, and connecting disparate systems.
- 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 with hands-on involvement in translation workflows.
- Strong understanding of how translation memory leverage, fuzzy matching, and terminology management drive productivity, with the judgment to set direction, prioritize asset-quality work, and be accountable for measurable gains.
- Working knowledge of professional translation workflows, including pre-translation, machine translation post-editing, revision, and quality assurance.
- Practical experience designing and operating integrations between systems, including application programming interface design, integration patterns, and monitoring.
- Demonstrated ability to work across engineering, operations, and business stakeholders in an agile environment and translate operational needs into technical specifications.
Responsibilities
- Build, lead, and develop a cross-functional team spanning engineering, automation, specialist linguistic-data, and analytics skills; set direction, prioritize work, and grow the team's capability and composition as the function matures.
- Establish engineering practices, delivery cadence, and quality standards appropriate for tooling that supports a high-precision translation environment.
- Own and prioritize the roadmap for professional translation workflow automation and internal tooling, 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 automation and workflow orchestration for professional translation using tools such as n8n and Apache Airflow, connecting production systems into reliable, auditable pipelines consistent with client confidentiality requirements.
- Treat translation memories and terminology as core productivity assets by driving translation memory leverage, fuzzy-match optimization, and terminology consistency.
- Direct the specialist work of maintaining, segmenting, and improving translation assets, and hold the team accountable for measurable gains in leverage and consistency.
- Unlock value from operational data beyond Phrase and Plunet by combining data from HubSpot, finance, quality assurance ticketing, and translation memories into analytics that show where to focus and prove impact.
- Improve data flow and integration across core production systems, including Plunet, Phrase, HubSpot, ATAI, and the Language Quality Assurance ticketing process, 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.
- Work directly with the Executive Vice President of Professional Translation and localization operations leadership to surface workflow gaps, quality risks, and automation opportunities, and translate them into clear technical requirements and delivery plans.
- Ensure solutions are designed for adoption by project managers, quoting, resources, linguists, revisors, desktop publishing, quality assurance, and finance.
- Define and track success metrics, including improved translation memory leverage and terminology consistency, reduced manual work, improved consistency, stronger quality assurance visibility, and faster turnaround.
Desired Qualifications
- Working familiarity with machine translation, large language model-based translation, or retrieval-augmented generation, enough to integrate and orchestrate around these systems and make sound decisions.
- Exposure to quality estimation, adaptive machine translation, or orchestrating large language model and retrieval-augmented generation components within production workflows.
- Familiarity with DevOps practices, including continuous integration and continuous delivery and infrastructure as code, and localization engineering.
- Experience in regulated industries such as legal, financial, or government environments where accuracy and data sovereignty are critical.
- Background in localization engineering, computational linguistics, or natural language processing.
- 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's Take
What believers are saying
- May 2026 capital raises added $23.4 million gross, extending runway into production.
- Headcount grew 54% to 57 employees, concentrating talent on validation and tooling.
- First five validation vehicles rolled off the line in May 2026, de-risking launch.
What critics are saying
- Aptera lost $10.2 million in Q1 2026; cash was only $17.7 million.
- Management needs follow-on dilution or ELOC draws before production proves economics.
- If certification slips, reservation demand and financing collapse before scale.
What makes Apertera unique
- Aptera’s three-wheel solar EV targets 40-mile daily solar charging, unlike mainstream EVs.
- June 2026 validation testing exceeded 4 kWh daily solar generation, proving the core gimmick.
- FTZ designation in February 2026 lowers import friction for Carlsbad assembly.
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Benefits
Hybrid Work Options