ML Engineering Lead

Who are we?

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, making 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.

Who We’re Looking For

As the Machine Learning Engineering Lead, you will guide the team responsible for creating and implementing our computer vision and other machine learning pipelines, used in predicting cell behaviour, developed with the Machine Learning Science team. Your main tasks include developing these pipelines 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, from pipeline deployment and scaling, all the way to productisation, ideally including integration into client facing applications, 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.

The interview process:

·      Preliminary telephone interview (30 mins)

·      Telephone interview to include 30 minutes Python coding assessment (60 mins)

·      Telephone conversation with the CEO (30 mins)

·      Open-ended ML questions, meeting the team (onsite in Bristol, 120mins)

Requirements

• 5+ years of experience as a Machine Learning Engineer, including experience working in a top tier tech, with a focus on taking pipelines 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
• Strong background in ML models and using modern frameworks for deploying these models, including in training and fine-tuning models and implementing continuous learning practices
• Experience of working within a collaborative multi-functional team environment
• Experience in architecting, building and maintaining scalable & distributed ML infrastructure, including big data pipelines, large-scale model training/inference, and serving infrastructure
• Experience in designing and developing robust backend APIs, integrating with client applications and machine learning models
• Excellent at communicating complex data insights in a clear and actionable way
• Familiar with cloud services (GCP is particularly relevant) and containerisation

Nice to haves

• Experience with DevOps practices and MLOps tools (Kubernetes, Apache Airflow)
• Experience in an AI bio company 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

A competitive salary in line with experience is on offer, as well as some great employee benefits:

·        Contributory pension scheme

·        Private healthcare and dental insurance

·        Life assurance

·        Flexible working

·        Regular team building events