AI Applied Researcher
Remote • Dublin
Posted 1d ago
Job Location
Dublin
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
Accenture Labs' AI R&D Team is seeking an Applied Scientist to bridge advanced AI research and real-world business impact. This role involves translating state-of-the-art machine learning and AI techniques into practical, scalable solutions for complex problems across various domains. You will own the end-to-end lifecycle of AI solutions, from problem formulation and experimentation to validation, deployment, and measuring outcomes. The position offers a unique blend of deep research and hands-on development, requiring the synthesis of the latest academic and industry research, adaptation of foundation and compact language models, and the design and implementation of agentic LLM systems.
Responsibilities
- Review, analyze, and summarize the latest academic and industry research in technical domains.
- Adapt foundation and compact language models to specialized domains using techniques like fine-tuning, continued pre-training, distillation, and parameter-efficient methods.
- Design and implement agentic LLM systems that integrate external tools (APIs, databases, services, rule engines) for precise and verifiable tasks.
- Collaborate with Senior Research Scientists to rapidly design, build, and test Proof-of-Concepts.
- Articulate complex research findings into clear, persuasive, and publishable papers and presentations.
- Craft engaging narratives and technical demonstrations to translate research outcomes into compelling value propositions.
Requirements
- Master's degree plus 2-3 years of industry experience or a PhD in Computer Science/AI (AI/ML/NLP focus) with 1-2 years of industry experience.
- Strong foundation in machine learning, including supervised learning, embeddings, evaluation metrics, and data preprocessing.
- Strong analytical and critical thinking skills.
- Good written and verbal communication abilities, with the capacity to structure presentations for clarity and impact.
- Expertise in experimental design, including designing controlled experiments, defining baselines, and interpreting results quantitatively.
- Ability to collaborate effectively with researchers, engineers, and product stakeholders in cross-functional environments.
- Ability to track, evaluate, and apply relevant research literature.
- Strong programming skills in Python, with experience in libraries like PyTorch (preferred) or TensorFlow.
- Ability to implement custom models (neural networks, transformers), layers, or loss functions.
- Hands-on experience building, adapting, and evaluating compact language models (SLMs), understanding domain adaptation, efficiency trade-offs, and deployment constraints.
- Experience integrating LLMs with external tools and systems to execute structured, multi-step tasks with high precision.
- Experience integrating external knowledge sources (databases, document collections, knowledge graphs, rule-based systems) into LLM/SLM systems.
- Demonstrated ability to combine model reasoning, external knowledge, and tools into reliable end-to-end systems.
Benefits
- Competitive base salary
- Pension
- Private health insurance
- Discounted gym membership
- Emergency caring facilities
- 2 days' leave per year for charitable work
- Flexible working arrangements can be discussed