AI Research Engineer

💻 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.

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

👍 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