AI Researcher (Internship)

AI Researcher (Part-Time, PhD Student, early-career researcher)  Location: Remote, with conference travel (U.S. or Europe preferred)  Engagement Type: Internship (Parttime) Department: TECH / R&D  About DATAmundi  DATAmundi builds advanced software solutions that power our localization and data services. We support AI companies and research teams by delivering high-quality datasets, validation workflows, and scalable data processing. Our R&D initiatives explore how modern AI systems — including LLMs, speech models, and multimodal systems — can be evaluated, improved, and safely deployed through structured data and validation methodologies.  We are expanding our R&D activities and seeking researchers to collaborate on applied research and technical outreach within the AI ecosystem.  Role Overview  DATAmundi is seeking a part-time AI Researcher (PhD student, doctoral candidate, or early-career researcher) in areas such as Agentic AI, Machine Learning, Natural Language Processing, or Speech Technologies.  The researcher will report directly to our CTO and contribute to internal research initiatives, co-author technical papers, and help prototype research systems related to machine translation, data validation, evaluation methodologies, and AI model performance. The role also includes technical communication activities such as writing educational technical content and participating in academic and industry conferences.  This position combines applied research, engineering experimentation, and academic engagement with the broader AI research community.  Key Responsibilities:  Research & R&D Contribution  Conduct applied research related to AI model evaluation, data quality, and validation methodologies  Co-author research papers, technical reports, and whitepapers  Implement research prototypes and experimental systems  Support internal R&D initiatives in areas such as Agentic AI systems, LLM evaluation and validation, Speech and multimodal model assessment, Data-centric AI methodologies  Collaborate with the engineering team to translate research ideas into practical workflows  Research System Implementation  Develop experimental code and proof-of-concept implementations  Work with datasets used for training, evaluation, and benchmarking  Design experiments and analyze results  Document methodologies and experimental findings  Technical Writing & Knowledge Sharing  Write technical blog articles explaining recent advances in AI and ML  Translate complex research topics into accessible technical content  Support marketing and communications teams with technically accurate material  Contribute educational materials and technical explainers  Conference Participation & Outreach  Attend academic and industry conferences  Engage with researchers from AI companies and academia  Discuss research topics, evaluation challenges, and data requirements  Identify opportunities for collaboration related to dataset needs and model evaluation  Maintain professional follow-up communication after conferences  Required Qualifications  Current PhD student, doctoral candidate, or recent graduate in:  Machine Learning/Artificial Intelligence/Natural Language Processing/Speech Processing/Computer Science or related field  Strong understanding of modern AI models (LLMs, speech models, or multimodal systems)  Experience implementing research code in Python  Familiarity with common ML frameworks  Ability to read and understand academic papers  Strong written English skills  Interest in applied research and real-world deployment challenges  Desired Skills / Experience  Research experience in Agentic AI, LLM evaluation, or model alignment  Experience preparing or submitting research papers and technical report  Experience working with datasets and benchmarking methodologies  Experience with speech datasets or audio processing  Experience with prompt engineering or evaluation frameworks  Public speaking or academic presentation experience  Interest in engaging with the research community  Ideal Profile  The ideal candidate:  Is comfortable discussing research topics with other researchers  Communicates clearly in technical discussions  Is proactive in networking within academic or industry conferences  Can represent technical concepts in a professional setting  Enjoys bridging academic research and real-world applications  Working Arrangement  Part-time engagement (flexible hours)  Remote collaboration with periodic meetings  Conference attendance (travel to conferences will be funded on relevant events defined with our CTO and Marketing department – e.g. ACL, Interspeech, NeurIPS, etc.)  Success Criteria  The researcher will be successful in this role by:  Contributing to research outputs (papers, reports, or prototypes)  Supporting internal R&D innovation  Producing high-quality technical content  Helping identify opportunities where data services can support research and model development  Establishing productive relationships within the AI research community