Wave Group
AI Research Engineer
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💻 Job Title: AI Research Engineer 💰 Salary: £80-150k (DOE)
- very generous equity (50% of your salary) 📈 📍 Location: Soho (3 office days/week) 🌴 Benefits: Unlimited annual leave + remote working around holidays if you wish 8% employer pension contribution Comprehensive health insurance £1,000 L&D budget to use as you see fit 📊 Industry: B2B - AI Research - Synthetic Data 👥 Team: ~30 💸 Funding: ~$15m (Series A) 🛂 VISA sponsorship available if needed
This early-stage, well-funded start up is building advanced AI systems that model and simulate complex real-world behaviour at scale. Their platform enables organisations to test decisions, scenarios and strategies using large-scale AI-driven simulations, dramatically reducing time-to-insight compared to traditional approaches.
Following a strong early traction and funding injection, they're looking for another AI Engineer with deep Research expertise to join a highly technical team of 6 working at the intersection of large language models, agent systems and scalable backend infrastructure.
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In this role, you’ll work across agent cognition, memory, reasoning and orchestration, while ensuring the underlying platform is performant, cost-efficient and production-ready. You'll be: formulating research questions about human / agent behaviour designing experiments on synthetic populations validating model behaviour against real-world data deciding what architectures and methods should exist, not just implementing them
The perfect candidate would ideally have experience with LLMs / agent development as well as backend engineering, but the most critical part of the role is definitely deep research expertise, making it ideal for someone who enjoys experimentation and research-driven iteration, but also cares about robust system design and real-world deployment.
✅ Must have requirements: PhD / MSc or substantial research experience in AI, ML, CS, Cognitive Science, Physics, Mathematics, or a related field Demonstrated ability to conduct independent, hypothesis-driven research Strong grounding in experimental design, statistical validation, quantitative evaluation Strong software engineering fundamentals in Python and backend frameworks like FastAPI, Flask, Django Hands-on experience working with ML / AI models (LLMs, NLP, simulation, or related areas) Comfortable working in ambiguity, where the right question is often unclear at the start
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👍 Bonus points for: Familiarity with fine-tuning workflows, model optimisation and experiment tracking Experience with multi-agent systems, simulations or agent-based modelling Experience building workflows/agents on top of existing models Experience with relational databases and vector search / embedding systems Knowledge of cloud infrastructure, containerisation and deploying ML systems to production Experience working in fast-moving environments with evolving requirements
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