ML Engineer

About us

Electric Twin is building advanced systems to predict human behaviour. Recent progress in computation and data science have allowed us to build a platform that enables rapid experimentation and better decision making.

The vision of Electric Twin is based on the principles of evolution - that humans operate rationally, but within a highly complex society beyond the comprehension of human analysis. Electric Twin looks to replicate complex decision making by using generative AI and real world data, enabling rapid predictions with high levels of accuracy.

We already help our design partners solve some of their most complex challenges in navigating modern-day decisions, including technological evolution, sustainability, healthcare crises and rapid changes in consumer sentiment.

We are backed by Europe's leading seed-stage investors and have assembled an exceptional team. We are looking for a driven ML engineer to work on improving our ability to predict human behaviour and play a central role in our work with customers.

Responsibilities

• Design and implement state-of-the-art machine learning models to predict human decision making.
• Propose areas of research to improve our ability to predict human behaviour, and the performance of our models and systems.
• Use focus group conversations, surveys and other contextual data in order to fine-tune language models to achieve better representations of target populations.
• Develop evaluation methodologies to de-blackbox LLM decision pathways for the underlying dataset.
• Successfully implement machine learning techniques to interpret and analyse data; iterate on feedback to improve the value of our models in customer use cases.

Requirements

• Experience of implementing and deploying machine learning research ideas within industry.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Strong statistical modelling experience with examples of using these in real-world applications.
• Proficiency in Python, with a focus on statistical, ML, data analysis and visualisation libraries: pandas, numpy, statsmodels, scikit-learn, pytorch.
• Deep Learning knowledge with examples of completing projects in this area.
• Keen interest in using LLMs.

Desirable

• Not afraid of using and developing unorthodox methods to make progress on difficult problems.
• Product-minded outlook: You can build for customers and iterate on their feedback.
• Startup mindset: You value the importance of moving quickly, getting things done and picking up tasks which are not on your to-do list.