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