Applied Machine Learning and AI Engineering Intern

Ricoh Americas Holdings•Boulder, CO

About The Position

Ricoh is seeking a highly motivated summer 2027 intern to help build an AI-powered globalization platform that translates product documentation and software into eleven languages. The translation process is moving from hybrid automation toward a fully in-house, AI-driven pipeline intended to reduce turnaround time from weeks to a day while improving translation quality and consistency. The intern will contribute during the validation and pilot phases, working on machine learning and engineering problems that help determine whether automated translations are reliable enough to ship to customers. This is applied work on a system with real users, measurable cost impact, and a path to production. Potential projects include developing translation-quality evaluation methods across languages; creating terminology checks for product and brand language; implementing delta translation to process only changed content; improving large language model translation of structured technical content while preserving XML tags and formatting; automating translation-package processing and source-control updates; and analyzing AI outputs and presenting findings to cross-functional teams.

Requirements

Be working toward an M.S. or Ph.D. in Computer Science, Computer Engineering, Data Science, Linguistics/Computational Linguistics, or a related field.
Be currently enrolled in an accredited graduate program, or completing an undergraduate degree and enrolled to continue education in an accredited graduate program.
Have a cumulative GPA of 3.0 or higher.
Successfully complete all required screenings before hire.
Have excellent Python programming skills and a good understanding of data structures, software design principles, and algorithms.
Have familiarity with AI/ML concepts, natural language processing, and data processing.
Have strong analytical and problem-solving skills, including the ability to design a fair evaluation of a system’s output.
Be able to work independently and collaborate with a team.
Have an interest in language technology, AI-driven automation, and process optimization.

Nice To Haves

Hands-on experience with large language models or generative AI APIs, including prompt design and output evaluation.
Experience using Claude and AI-assisted development workflows in Visual Studio Code, or comparable AI developer tooling.
Experience with machine translation, internationalization/localization, or multilingual datasets.
Familiarity with structured document formats such as XML, DITA, JSON, or YAML, and text parsing.
Experience with cloud services such as AWS and building or consuming REST APIs.
Working knowledge of Git and standard software development workflows.
Reading or speaking proficiency in a second language, particularly Japanese, German, French, Spanish, Chinese, or Korean.
Skill in explaining and presenting analyses and machine learning concepts to a broad technical audience.

Responsibilities

Contribute working code to an active engineering project alongside full-time engineers.
Design and execute experiments to evaluate model and pipeline performance, and document the results.
Collaborate with teams across documentation, software development, and infrastructure.
Present progress and final results to technical stakeholders and department leadership.
Build or run evaluation methods for machine translation quality across multiple languages.
Develop a terminology checker to enforce product terminology and brand language consistently.
Implement delta translation to detect and translate changed content.
Work with large language models to improve translation accuracy on structured technical content while preserving tagging and formatting.
Help automate the end-to-end translation pipeline, including package intake, processing, and checking completed translations into source control.
Analyze and refine AI outputs to improve accuracy and usability, and present findings to development, documentation, and localization teams.