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TU
Programmer Analyst I-2
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Senior AI/ML Software Engineer – Localization
NEARSOURCE TECHNOLOGIES
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- Full-time
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NEARSOURCE TECHNOLOGIES

Senior AI/ML Software Engineer – Localization

Vancouver, BC, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 13, 2026
Posting language: English
Posted: Nov 13, 2026

Original job description

Job Title: Senior AI/ML Software Engineer – Localization

Job Location: Hybrid – Vancouver, BC, Canada

Job Type: T4 Contract

Experience: 6+ Years

Rate: CAD 70 - 75 per hour

Role Summary: NearSource is seeking a Senior AI/ML Software Engineer - Localization to architect and scale intelligent localization systems using advanced AI, Natural Language Processing (NLP), and machine translation technologies.

The role will focus on developing production-ready AI-powered localization pipelines, fine-tuning transformer-based models, and delivering scalable backend solutions that enhance translation quality, automation, and enterprise localization workflows.

Key Responsibilities

AI-Powered Localization Architecture

Architect advanced localization workflows integrating Neural Machine Translation (NMT) and Large Language Models (LLMs) for translation refinement.
Design and implement reference-free Quality Estimation (QE) systems using COMET, BLEURT, or custom LLM-based evaluators.
Develop and fine-tune Automated Post-Editing (APE) solutions to improve translation fluency, terminology accuracy, and stylistic consistency.
Fine-tune transformer-based models using Hugging Face and domain-specific translation memory and glossary data.

Backend Engineering and System Integration

Architect and develop scalable backend services, APIs, and microservices supporting automated localization workflows.
Design integrations across product systems, Translation Management Systems (TMS), content repositories, and CI/CD pipelines.
Develop automation frameworks for content extraction, file processing, translation handoffs, validation, and linguistic quality assurance.
Optimize model inference, performance, and cloud deployment using AWS services, including SageMaker and Bedrock.

Data Engineering and NLP

Develop Python-based pipelines for multilingual data curation, sentence alignment, tokenization, and fuzzy matching.
Benchmark translation performance using BLEU, chrF++, TER, COMET, and other NLP evaluation metrics.
Drive workflow optimization through intelligent automation, data processing enhancements, and scalable system architecture.

Technical Leadership

Establish technical standards for localization engineering and AI-driven translation quality.
Partner with Localization Program Management and product engineering teams to align technical execution with localization strategy.
Provide technical guidance on localization tooling, automation frameworks, and AI-enabled localization practices.
Contribute to the evolution of shared localization platforms, engineering tools, and technical standards.

Must-Have Skills

6+ years of software engineering experience with a strong focus on backend engineering or AI/ML development.
Strong proficiency in Python and hands-on experience with transformer-based models, including Hugging Face or similar frameworks.
Experience training, fine-tuning, and deploying machine learning models using AWS services such as SageMaker or Bedrock.
Strong experience designing and developing APIs, microservices, and system integrations.
Strong understanding of end-to-end localization workflows, including content extraction, translation, review, quality assurance, and release.
Hands-on experience with Translation Management Systems (TMS), such as Phrase, Passolo, or similar platforms.
Experience working with SQL/NoSQL databases and cloud-native architectures.

Nice-to-Have Skills

Experience implementing reference-free Quality Estimation (QE) or Automated Post-Editing (APE) solutions.
Familiarity with LLM orchestration frameworks such as LangChain.
Experience integrating localization workflows into CI/CD pipelines.
Knowledge of automated linguistic quality assurance and validation tools.
Background in NLP, computational linguistics, or multilingual data engineering.
Experience optimizing model inference performance and cost efficiency in production environments.

Interview Process

The selection process is expected to include 2-3 interview rounds:

Round 1: 30-minute Hiring Manager discussion.
Round 2: Technical interview focusing on AI knowledge, system design, and coding.
Additional Round (if required): Behavioural or technical assessment based on the candidate's profile and interview feedback.

Apply now, or share your resume with salary expectations at careers@nearsource.ca. Thank you for considering a career with NearSource! Once you submit your application, our Talent Acquisition team will review your resume thoroughly. If there's a strong match, we'll reach out to discuss your experience, role details, benefits, compensation, and next steps. While we strive for transparency, we may not be able to respond to every applicant due to high volume, but we genuinely appreciate your time and interest.

About NearSource: NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives.

Equal Opportunity Statement: NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.

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More about this job

Responsibilities

Architect and build AI-powered localization pipelines using machine translation, large language models, quality estimation, and automated post-editing. Develop scalable backend services and multilingual data pipelines, optimize cloud-based model deployment, and provide technical leadership for localization engineering practices.

Requirements

Requires at least six years of software engineering experience, strong Python and transformer-model expertise, and experience training and deploying models on AWS. Candidates should also have backend API and microservices experience, knowledge of end-to-end localization workflows, and hands-on experience with a Translation Management System.

Skills

Python
Artificial Intelligence
Machine Learning
Natural Language Processing
Transformer Models
Hugging Face
AWS SageMaker
AWS Bedrock
Backend Engineering
API Development
Microservices
Localization Workflows
Neural Machine Translation
Quality Estimation
Automated Post-Editing

Visa sponsorship

Not detected in the job text

Keywords

Python
Artificial Intelligence
Machine Learning
Natural Language Processing
Large Language Models
Neural Machine Translation
Transformer Models
Hugging Face
AWS SageMaker
AWS Bedrock
Quality Estimation
COMET
BLEURT
Automated Post-Editing
Phrase
Passolo
APIs
Microservices
SQL
NoSQL
Multilingual Data Curation
Sentence Alignment
Fuzzy Matching
BLEU
chrF++
TER
CI/CD
LangChain
Cloud-Native Architecture

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