Data Scientist / Machine learning engineer
Twyn, United Kingdom

Twyn is a revolutionising platform fostering conversational interactivity in real-time and at scale. As of today, we have two live applications an English and a surfing learning app. We are now extending our offering with a unique conversational experience with the football icon Messi.

We are dependent on state-of-the-art technologies in a number of areas, including Natural Language Processing (NLP), Large Language Models (LLMs), speech recognition and traditional Machine Learning (ML). Our systems are built on advanced foundations with proprietary extension and optimisation. We have been recently using open-source transformer language models alongside LLMs to foster interactive and engaging user conversations.

Requirements

What You'll Do:

• Execute an Ramp;D programme to develop machine learning components and other advanced technologies for integration into the Twyn platform. Our systems generally leverage third-party technologies such as transformers or LLM models, augmented by proprietary extensions and optimisations.
• Systematically and quantitatively characterise and optimise candidate technologies, including acquiring necessary data sets and appropriate statistical analysis.
• Document your findings for internal consumption, e.g., as Jupyter notebooks.
• Advise the product engineering teams on the effective implementation of your research findings.

What You'll Bring:

• A Masters or PhD degree in Computer Science or a related quantitative field, or extensive industry experience with an in-depth understanding of the ML field.

• Hands-on experience in AI research and development, with exposure to key technologies like machine learning, deep neural networks, language modelling, and conversational AI.
• Demonstrated adaptability across various research subjects and a broad interest in diverse topics.
• Significant software engineering experience in Python, and familiarity with standard tools (GitHub, Jupyter) and libraries (NumPy, Scikit-learn, hugging-face).
• Strong quantitative and statistical analysis skills.
• Although software engineering support will be provided, you will be expected to be capable of writing your own research code. The ability to write production-grade code and contribute to data and machine learning engineering would also be useful.

Benefits

• Negotiable competitive salary.
• Opportunity to receive equity in the company as part of your compensation.
• Remote work (with occasional travel to London) and flexible hours.
• High levels of autonomy and minimal policy constraints (see 'No Rules Rules' by Reed Hastings and Erin Meyer).
• A unique opportunity to join an early-stage company backed by a highly experienced leadership team.

Job Rewards and Benefits