AI ML Engineering Internship

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

MAIN PURPOSE OF JOB
The AI/ML Engineering Intern assists with the AI team to design, prototype, and deploy AI 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.

MAIN DUTIES:
• Assist in well-defined pieces of work around research & development. Contribute to model and algorithm design using state of the art AI techniques such as large-language-models (LLM).
• Contribute to rigorous evaluation of AI 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 AI 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 AI-related 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
• Learning Curve & Initiative: Willingness to learn. Demonstrate skill growth and ownership of small tasks from start to finish.
• Code Quality & Reproducibility: Well-structured, testable Python code and clearly documented experiments.
• Collaboration: Timely communication of progress and blockers. Thorough documentation of deliverables.
• Impactful Contributions: Measurable improvements in model accuracy, runtime efficiency, or tooling.

REQUIREMENTS:
• Education
• Completed or actively pursuing a BSc or MSc in Computer Science, Data Science, AI, or a related field (final-year undergraduates welcome).
• Technical Foundation
• Coursework or personal projects in AI, machine learning or NLP, solid 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
• Clear written and verbal English communication, curiosity, problem-solving attitude, and willingness to ask questions.