Adecco
Research Engineer
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Job Title: Research Engineer – Fundamental AI Research
Location: London, UK (Hybrid)
Position Type: 12 months contract
Salary: £90,000 per year
About the Role
We are seeking a Research Engineer to join a premier, world-class Fundamental AI Research organization. This team is dedicated to advancing the state of artificial intelligence by solving fundamental systems challenges to accelerate our reach toward Advanced Machine Intelligence.
Unlike traditional contingent roles focused strictly on isolated infrastructure or annotation tasks, this position offers true research embedment. You will operate as a deeply integrated member of a frontier research lab, collaborating directly alongside junior and senior staff scientists to build, experiment, and solve core AI research problems at scale.
The primary research focus centers on recursive self-improvement—building advanced AI systems that build AI to accelerate development.
Key Responsibilities
- Advance ML Systems: Design and code methods, tools, and infrastructure to push forward the state of the art in Large Language Models (LLMs) and generative AI.
- Recursive Self-Improvement Research: Build complex reinforcement learning (RL) environments, generate high-quality synthetic data to elevate model performance, and research multi-agent systems where multiple AIs collaborate.
- Robust Infrastructure & Sandboxing: Develop functional, secure, and reliable sandboxes and pipelines that allow AI agents to operate safely and effectively.
- Scientific Rigor & Debugging: Execute complex experiments involving large models and datasets. Apply a rigorous scientific framework to debug complex agent traces and understand why approaches succeed or fail.
- Stay at the Cutting Edge: Keep pace with rapid industry developments by reviewing literature, synthesizing research findings, and translating insights into technical deliverables.
- Adaptability: Work effectively in a high-velocity, dynamic research environment, maintaining high output even when priorities pivot to support critical high-priority models.
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Candidate Requirements
Non-Negotiable Skills & Experience
- Hands-on experience in Machine Learning, Artificial Intelligence, Recommendation Systems, or Pattern Recognition.
- Proven experience developing and scaling machine learning models (e.g., programmatically querying LLMs, LLM post-training, or conducting research at scale).
- Advanced programming skills in Python and hands-on expertise with frameworks such as PyTorch.
- Experience executing complex scientific experiments involving large AI models, datasets, and complex agent systems.
- Comfort working in high-ambiguity environments with shifting research priorities.
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Education
- Minimum Requirement: Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field.
- Preferred: PhD or research-focused Master’s degree in Machine Learning, AI, or a closely related field (candidates currently completing their PhD are welcome to apply provided they can meet full-time hours).
Nice-to-Have Skills
- Direct, hands-on experience in Generative AI and LLM research.
- Background in developing multi-agent systems or reinforcement learning environments.
Why Apply?
- Frontier Research Access: Direct exposure to high-stakes, cutting-edge research environments that are rare in today's AI landscape.
- Full Integration: Function as a core contributor to actual research initiatives rather than being siloed into standard contractor duties.
- Publication Potential: Opportunity to contribute to and be credited on major technical papers alongside senior researchers (subject to organizational publication policies).
- Accelerated Skill Development: Deepen your expertise in agent trace debugging, multi-agent dynamics, synthetic data generation, and large-scale model architectures.
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