Electric Twin - Research Engineer

London - Hybrid+ Equity2w ago

In Office Junior EMEA Artificial Intelligence Nonprofit Research Engineer Python FastAPI Django Flask Hugging Face

Requirements

• Bachelor's or Master's degree in CS, Math, Physics, AI, or related technical field. • Strong foundation in both AI/ML concepts and backend engineering principles. • Experience working in fast-paced environments where requirements evolve rapidly. • Over 7 years of experience with at least 1 year working hands-on with large language models to solve complex problems. • Proof of fast iteration and experimentation in order to validate model performance and outputs. • Exposure to research-driven product development or academic AI research is desirable. • Knowledge of fine-tuning workflows, model optimisation, and experiment tracking. • Understanding of statistical validation and data quality assessment. • Experience with frameworks for building AI / LLM applications (e.g. PyTorch, Hugging Face Transformers, LangChain). • LLM & Agent Development: • Hands-on experience building applications with large language models, implementing advanced prompting techniques, RAG systems, and agentic workflows. • Experience with multi-agent systems, simulation frameworks, or agent-based modelling. • Backend Engineering: • Proficient in Python and backend frameworks (e.g. FastAPI, Django, Flask); understanding of distributed systems and scalable architectures. • Personal Attributes • Personal Attributes • Strong ownership mentality—you see projects through from design to deployment. • Pragmatic problem-solver who balances technical elegance with business needs. • Clear communicator who can explain complex technical decisions to non-technical stakeholders. • Thrives in ambiguity and adapts quickly as product requirements evolve. • Passionate about building infrastructure that enables innovative AI applications. • Intellectually honest—willing to question prevailing approaches and advocate for better solutions when evidence supports it. • Collaborative mindset—debates ideas vigorously while respecting other perspectives.

Responsibilities

• There are three main areas that members of the science team focus on: • Research, Modelling and Experimentation: You will design and run systematic experiments to evaluate synthetic agent behaviour, test hypotheses about behavioural patterns, and iterate on model architectures based on empirical results and validation against real-world data. • Research, Modelling and Experimentation: • LLM Product Engineering: You will build sophisticated prompting strategies, behavioural frameworks, and decision-making systems that enable agents to exhibit realistic human-like behaviour across diverse scenarios and demographics. You will combine this with client interactions to ensure product viability for the end customer. • LLM Product Engineering: • Architecture & Development: Design and implement the cognitive systems that give AI agents consistent personalities, memory, and reasoning capabilities, using advanced LLM techniques like chain-of-thought prompting, RAG systems, and agentic tool use. • Architecture & Development:

Benefits

• We offer a competitive package designed to support you properly, not just on paper. • Meaningful equity in a high-potential seed-stage company. • Unlimited leave. Take the time you need. • Generous matched pension contributions. • Private healthcare. • Cycle to work scheme. • Direct access to and collaboration with world-class founders. • Hybrid working from our London office (4 days in office a week). • Flexible working around life commitments. We value outcomes over presenteeism.