Research Engineer – Generative AI / LLMs / Agentic Systems / Research Engineering
We are currently partnered with a global technology and research organisation developing advanced artificial intelligence, large language model, and intelligent computing technologies.
As part of their continued investment in AI agent research, they are looking to hire a Research Engineer – AI Agents & LLM Systems to design, build, and evaluate advanced AI-agent systems capable of reasoning, planning, interacting with tools, and completing complex tasks.
This is a hands-on research engineering role for someone who enjoys turning uncertain research questions into working systems. The successful candidate will combine strong software engineering with research judgement, taking ownership of problems from initial objective definition through prototyping, experimentation, evaluation, failure analysis, and system improvement.
Key responsibilities
- Design and implement AI agents based on large language models and multimodal foundation models
- Build systems involving tool use, planning, memory, retrieval, code execution, computer use, and multi-step workflows
- Develop advanced agent architectures capable of reasoning, planning, and completing complex tasks
- Design rigorous evaluation environments, benchmarks, and failure-analysis tools for agent capabilities
- Rapidly prototype new research ideas and turn promising approaches into robust, reusable implementations
- Reproduce and critically evaluate methods from recent AI research
- Run controlled experiments and make evidence-based technical decisions
Key requirements
- MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience
- Strong Python programming and software engineering skills
- Experience building non-trivial machine learning or AI systems
- Practical knowledge of large language models, transformers, and modern generative AI systems
- Experience with PyTorch or an equivalent deep learning framework
- Ability to design meaningful experiments and evaluate systems objectively
- Strong debugging, analytical, and problem-solving skills
- Two or more years of relevant industry or applied research experience
- Experience building tool-using agents, coding agents, computer-use agents, or other multi-step LLM systems
- Experience with LLM evaluation, trajectory analysis, reinforcement learning, post-training, or synthetic-data generation
Keywords
Research Engineer / AI Research Engineer / AI Agents / LLM Systems / Agentic AI / Generative AI / Large Language Models / LLM / Multimodal AI / Foundation Models / Transformers / AI Systems / Machine Learning / Machine Learning Systems / Tool Use / Tool-Using Agents / Planning / Reasoning / Memory / Retrieval / Code Execution / Computer Use / Multi-Step Agents / Coding Agents / Computer-Use Agents / LLM Evaluation / Agent Evaluation / Benchmarking / Trajectory Analysis / Failure Analysis / Reinforcement Learning / Post-Training / Synthetic Data / Open-Source LLMs / LLM Serving / Model Optimisation / PyTorch / Python / TypeScript / Software Engineering / Research Engineering / AI Research / Experimental Design / Performance Optimisation / Latency / Cost Optimisation / AI Infrastructure / Research Prototype / AI Systems Development / Machine Learning Engineering / Generative AI Research
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