AI Researcher (Part-Time, PhD Student, early-career researcher)
Location:Remote, with conference travel (U.S. or Europe preferred)
Engagement Type: Internship
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 asAgentic 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
Originally posted on