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
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