INTERNSHIP DETAILS

AI Machine Learning Engineering Intern

CompanyWelocalize
LocationThessaloniki
Work ModeOn Site
PostedJanuary 14, 2026
Internship Information
Core Responsibilities
The AI/ML Engineering Intern assists the AI/ML team in designing, prototyping, and deploying machine-learning solutions. They contribute code, experiments, and ideas while gaining hands-on experience with cloud infrastructure and production best practices.
Internship Type
full time
Company Size
5643
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
For over 25 years, Welocalize has helped some of the world's largest organizations improve customer engagement through the power of localized content. Since our founding in 1997, we've been a leader in applying innovative technology and adopting AI to deliver the highest quality translations quickly, efficiently, and at scale. Our proven track record showcases tangible business outcomes, including higher marketing conversion rates, regulatory compliance, increased customer satisfaction and retention, intellectual property protection, higher adoption rates, and improved data with enhanced models. At the heart of our innovation is OPAL, our advanced Service Delivery Platform, ensuring every translation is fast, effortless, and impeccably accurate. This technology, combined with our extensive network of over 250,000 linguistic experts in more than 250 languages, allows us to deliver multilingual content transformation services that are unmatched in quality and relevance. Our global team of industry specialists is dedicated to enabling your teams to achieve global business outcomes. From translation and localization to NLP-enabled machine learning training data, and data annotation, we blend cutting-edge technology with human insight across every project.
About the Role

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Job Responsibilities:

The AI/ML Engineering Intern assists with the AI/ML team to design, prototype, and deploy machine-learning solutions that enhance Welocalize’s localization and business-workflow products. They contribute code, experiments, and ideas while gaining hands-on experience with cloud infrastructure and production best-practices, supported by dedicated mentors.

Key Responsibilities

• Assist in well-defined pieces of work around research & development. Contribute model and algorithm design using state of the art machine learning techniques such as large-language-models (LLM).

• Contribute to rigorous evaluation of ML models and systems. Choose the appropriate metrics for the assigned task.

• Support the setup of reproducible experiments in Python, following best processes for experimental tracking

• Assist with tasks like data cleaning, feature engineering, and building baseline models.

• Contribute to documentation by maintaining concise experiment logs, clear code comments, and short write-ups.

• Help the team stay up to date by reading recent papers or exploring new tools, and summarizing key insights.

• Participate in internal demos, team discussions, and code reviews to gain experience and contribute where possible.

Success Indicators
1. Learning Curve & Initiative: Willingness to learn. Demonstrate skill growth and ownership of small tasks from start to finish.
2. Code Quality & Reproducibility: Well-structured, testable Python code and clearly documented experiments.
3. Collaboration: Timely communication of progress and blockers. Thorough documentation of deliverables.
4. Impactful Contributions: Measurable improvements in model accuracy, runtime efficiency, or tooling.

Minimum Qualifications
• Education: Completed or actively pursuing a BSc or MSc in Computer Science, Data Science, or a related field (final-year undergraduates welcome)
• Technical Foundation: Coursework or personal projects in machine learning or NLP, solid Python fundamentals, hands on experience with LLMs
• Tools & Frameworks: Familiarity with at least one ML library such as scikit-learn, TensorFlow, or PyTorch, experience with Git. Basic knowledge of Docker or cloud services is a plus.
• Soft Skills: Clear written and verbal English communication, curiosity, problem-solving attitude, and willingness to ask questions.

Additional Job Details:

Key Skills
Machine LearningPythonData CleaningFeature EngineeringLarge Language ModelsExperimental TrackingDocumentationCollaborationProblem SolvingCommunicationGitTensorFlowPyTorchScikit-learnDockerCloud Services
Categories
TechnologyData & AnalyticsEngineeringSoftwareConsulting