As a trusted global transformation partner, Welocalize speeds up companies’ international growth by helping brands connect with, engage, and expand their global audiences. The company provides multilingual content transformation services—including translation, localization, and adaptation—in more than 250 languages, supported by a network of over 400,000 linguists worldwide. Welocalize also drives innovation in language services by delivering high‑quality training data solutions for NLP-driven machine learning, combining technology and human expertise to collect, annotate, and evaluate all types of content. Teams operate across North America, Europe, and Asia, serving clients in the regions most important to their business.

To perform this role effectively, an individual must be able to satisfactorily carry out each essential responsibility. The requirements below reflect the necessary knowledge, skills, and abilities. Reasonable accommodations may be provided to support individuals with disabilities in fulfilling these functions.

MAIN PURPOSE OF THE ROLE
The AI/ML Engineering Intern works with the AI team to design, prototype, and deploy AI solutions that improve Welocalize’s localization and workflow products. The intern contributes code, experiments, and ideas while gaining practical experience with cloud infrastructure and production best practices, guided by dedicated mentors.

MAIN RESPONSIBILITIES
• Assist with clearly defined research and development tasks, contributing to model and algorithm design using advanced AI methods, including large language models.
• Help evaluate AI models and systems using appropriate metrics for each assigned task.
• Support the setup of reproducible Python experiments, following best practices for experiment tracking.
• Contribute to tasks such as data cleaning, feature engineering, and building baseline AI models.
• Maintain documentation through concise experiment logs, clear code comments, and brief summaries.
• Stay current with recent AI papers and tools, sharing key takeaways with the team.
• Participate in internal demos, discussions, and code reviews to gain experience and contribute where possible.

Success Indicators:
• Learning & Initiative: Demonstrates growth, curiosity, and ownership of small tasks from start to finish.
• Code Quality & Reproducibility: Produces structured, testable Python code with well-documented experiments.
• Collaboration: Communicates progress and blockers promptly and documents deliverables thoroughly.
• Meaningful Contributions: Delivers measurable improvements in model performance, efficiency, or tooling.

REQUIREMENTS
• Education: Completing or pursuing a BSc or MSc in Computer Science, Data Science, AI, or a related field (final‑year undergraduates welcome).
• Technical Background: Coursework or personal projects in AI, machine learning, or NLP; strong Python fundamentals; hands‑on experience with LLMs.
• Tools & Frameworks: Familiarity with at least one AI/ML library such as scikit‑learn, TensorFlow, or PyTorch; experience with Git; basic knowledge of Docker or cloud services is a plus.
• Soft Skills: Strong written and verbal communication in English, curiosity, a problem‑solving mindset, and a willingness to ask questions.

Artificial intelligence tools may be used to support parts of the hiring process, such as reviewing applications, analyzing resumes, or evaluating responses. These tools assist the recruitment team but do not replace human decision-making. All final hiring decisions are made by people. For more information about how your data is processed, please contact us.