Machine Learning Engineer (NLP) in South West London - Eilla AI

Job DescriptionAbout UsOur mission at Eilla AI is to redefine one of the world's most complex workflows - the one of investors and investment bankers. We're developing a platform for mergers and acquisitions (M&A), venture capital (VC) and private equity (PE) professionals powered by large language models (LLMs) to seamlessly deliver accurate research and analysis. Recently fundraised and already working with leading financial institutions, we want to unlock efficiencies across every stage of the deal workflow in private markets. Join a world-class team with extensive AI and Finance experience on this exciting journey to reshape the future of the industry.About YouIf you: want to be an integral part of a fast-paced AI startupare self-motivated with a willingness to take ownership of taskshave a passion for shipping quality productsare a team player – willing to do a variety of tasks that move the team forwardlike tackling complex problems and adapting to unexpected challengesare a culture builder with a strong sense of integrityare excited about developing cutting-edge ML solutions… and thrive on pushing boundaries and achieving ambitious goals, we’d love to hear from you.Qualifications3+ years of relevant Data Science/ ML experience at product-driven companies. Solid experience with deep learning libraries such as Transformers, PyTorch, TensorFlow, Jax, or Keras.Proficiency in Python, with a strong grasp of Git workflows & commitment to best coding practices.Ability to leverage cloud computing environments including distributed clusters and GPUs.Demonstrated ability to deploy ML applications using containerization technologies is a bonus.ResponsibilitiesDevelop and refine scalable machine learning libraries tailored to the financial sector's needs.Write, document, and maintain modular code bases, ensuring quality and sustainability in collaboration with our engineering team.Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.Design and implement machine learning models to parse and learn from diverse data sets, including but not limited to textual, tabular, and graph data, optimizing for the financial domain.Harness the capabilities of Large Language Models (LLMs) to create industry-specific solutions, from proof of concept to fully-fledged deployed applications.BenefitsHighly competitive salary. Highly competitive equity package. Bonus based on performance. 25 vacation days per year + Bank Holidays. Generous tech equipment budget.