CellVoyant is an AI-first biotechnology company that predicts stem cell differentiation using live cell microscopy and artificial intelligence. We use this approach to optimise and unlock human tissue manufacturing for research and therapeutics applications. We aim to understand and solve important health issues, make a long-lasting positive impact on society and change the world.

We spun out from the Carazo Salas lab at the University of Bristol in 2022 and are backed by venture capital firms who were the earliest investors in DeepMind, Exscientia, Recursion, Automata, Wayve, and Abcam.

As the Lead Machine Learning Engineer, you will guide the team responsible for creating and implementing our computer vision and other machine learning models used in predicting cell behaviour developed with the Machine Learning Science team. Your main tasks include developing these models and putting them into use. You will also play a crucial role in the planning and development of our machine learning infrastructure. Additionally, you will coordinate with the Biology team, who conduct cell biology experiments and work on collecting microscopy data and developing protocols for cell differentiation.

You will have deep experience as a Machine Learning Engineer, with strong knowledge in computer vision models and how to use current MLE frameworks for deploying these models. Plus, you will have strong software engineering skills to handle infrastructure and scaling issues effectively.

You will build software that the Biology team uses to store, and analyse microscopy data, and that the Machine Learning team uses to build, integrate, test and scale ML features for production.

Our team is currently formed of 10 people, and you will have 3 to 4 direct reports to lead and mentor.

·        Initial phone screening (2x30 mins)

·        Python coding interview 60min, remote

·        Open-ended ML questions, meeting the team (onsite, 120min)

Requirements

·        5+ years of experience as a Machine Learning Engineer, including experience working in a top tier tech or AI-bio company, with a focus on taking models from concept to production.

·        Proven leadership in technical involvement and guidance of a team of ML and software engineers, including project planning, mentoring, and implementing agile methodology.

·        Experience in supporting/leading MLOps and Data Engineer operations and teams.

·        Strong background in computer vision ML models and using modern frameworks for deploying these models.

·        Experience of working within a collaborative multi-functional team environment.

·        Proficient in Python, and familiar with deep learning frameworks like PyTorch (required) and Tensorflow.

·        Skilled in using cloud services, containerisation, handling distributed systems, and familiar with continuous integration, unit testing, and code review practices.

·        Experience in architecting and maintaining scalable ML infrastructure, including big data pipelines, large-scale model training/inference, and serving infrastructure, as well as experience implementing best practices for  retraining, version control, reproducibility, and automation.

·        Excellent at communicating complex data insights in a clear and actionable way.

·        Experience with DevOps practices and MLOps tools (Kubernetes, Apache Airflow)

·        Experience in a biotechnology company or a background in biology are not necessary, but a genuine interest in this area will be of benefit.

·        Experience and desire to research relevant scientific publications.

Benefits

Join a rapidly growing technology company backed by world-class venture capital firms to work at the cutting-edge of artificial intelligence, stem cell biology, empirical large-scale experiment automation, and cell therapy development. Join a dynamic, inclusive, collaborative and intellectually stimulating culture that puts science at the forefront of everything we do. Be part of a world class, diverse, and inclusive team of experienced and interdisciplinary scientists applying their skills to some of the most impactful problems in human health. Competitive salary and founding equity compensation. Ability to work hybrid or in our Bristol, UK headquarters and join bi-annual week-long company off sites.