Data Scientist, Agentic Ai Developer, Full Stack Developer

Data Scientist, Agentic AI Developer, Full Stack Developer
Location: Trinity College Dublin, Dublin, Ireland
Department: ADAPT SFI Centre, School of Computer Science and Statistics
Contract: 12-Month Research / Specialist
These roles focus on designing, building, and deploying advanced AI and software solutions within a multi-agent, art-focused platform.
You will work across three integrated tracks: autonomous agent development, foundational multimodal modeling, and full-stack platform development.
Data Scientist
About the Role
The AI Research Scientist will architect and implement domain-specific Large Multimodal Models (LMMs) for the art world.
This system will support expert-level visual analysis, attribute extraction, and context-aware generative tasks.
You will apply state-of-the-art generative models and techniques such as transfer learning and parameter-efficient fine-tuning (e.g., LoRA).
A key part of the role involves developing RLHF pipelines to align model outputs with the evaluative heuristics of art experts.
Key Responsibilities
Architect Domain-Specific LMMs: design, pre-train, and fine-tune multimodal architectures for deep art analysis.
Develop Generative AI Pipelines: build generative systems using diffusion models and StyleGAN variants for art-related tasks.
Implement Adaptive Learning: use domain adaptation, meta-learning, and few/zero-shot strategies for evolving art categories.
Optimize Fine-Tuning: employ parameter-efficient training to adapt models while managing resources.
Design Human-Aligned Reasoning: run RLHF pipelines with input from art historians and curators.
Translate Research to Product: prototype, benchmark, and productionize innovations into APIs and MLOps pipelines.
Cross-Disciplinary Collaboration: work with art experts to define ontology schemas, annotation protocols, and evaluation rubrics.
Qualifications & Experience
At least 4 years of AI/ML/data science experience; Master's or PhD in Computer Science, AI, or related field.
Strong background in deep learning, computer vision, Python, and ML frameworks (e.g., PyTorch).
Experience with vision-language models and generative models (e.g., CLIP, GANs, diffusion).
Familiarity with fine-tuning methods (LoRA) and RLHF.
A portfolio of published research or notable projects in generative AI or computer vision.
Experience deploying ML models in production (MLOps, Docker, cloud platforms).
Prior experience at the intersection of art and technology or with cultural heritage datasets.
Agentic AI Developer
About the Role
This role focuses on designing, building, and deploying autonomous AI agents that orchestrate tasks within the platform.
Key Responsibilities
Architect Agentic Systems: design a scalable, asynchronous multi-agent framework for robust communication, task delegation, and coordinated execution.
Develop Specialized AI Agents: build agents for tasks such as client profiling, personalized marketing, and automated sales outreach.
Integrate External Services: work with third-party APIs (e.g., social media, CRM) to empower agents with tools and data.
Implement Advanced RAG Pipelines: engineer Retrieval-Augmented Generation systems using vector/graph databases for real-time context.
Research and Prototype: explore hierarchical agent structures and novel planning algorithms.
Collaborate and Deploy: work with product and research teams to translate AI capabilities into features and participate in the MLOps lifecycle.
Qualifications & Skills
Master's or PhD in Computer Science, AI, or related field.
Strong Python backend development experience and experience with multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI).
Proficiency with RESTful or GraphQL APIs and cloud deployment.
Experience deploying ML models in production (MLOps) and familiarity with vector/graph databases (e.g., Pinecone, Neo4j).
Portfolio of projects in AI/agentic frameworks and prior art/creative domain experience.
Full-Stack Developer
About the Role
The Full Stack Developer builds the user-facing platform and backend infrastructure enabling interaction with AI agents and models.
Emphasis on UX/UI to translate AI capabilities into practical features for art historians, galleries, and collectors.
Key Responsibilities
Front-End Development: build and maintain the user-facing components using React.
Backend Development: implement server-side logic and APIs using Python and Node.js.
Database Management: design and maintain PostgreSQL databases.
Systems Integration: integrate autonomous agents and multimodal models via RESTful/GraphQL APIs.
UX/UI Implementation: deliver intuitive user experiences; translate design concepts into features.
Deployment and Maintenance: participate in the full MLOps lifecycle for production systems.
Qualifications & Skills
Proven experience in a full-stack development role.
Strong front-end skills, particularly React; strong back-end skills in Python and Node.js.
Experience with relational databases and RESTful/GraphQL APIs.
Cloud deployment experience and ability to work in a collaborative, fast-paced environment.
Prior art at the intersection of art/creative domains is a plus.
We are seeking candidates who can contribute across multiple disciplines to advance AI-powered art market platforms.
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