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AI Machine Learning Lead

2 months ago

Bristol, Bristol, United Kingdom CellVoyant Full time
About CellVoyant

CellVoyant is a pioneering biotechnology company that leverages artificial intelligence to predict stem cell differentiation using live cell microscopy. Our innovative approach optimizes and unlocks human tissue manufacturing for research and therapeutic applications, aiming to address significant health issues and make a lasting positive impact on society.

Job Summary

We are seeking a highly experienced Machine Learning Engineer to lead our team responsible for developing and implementing computer vision and machine learning models. As the Lead Machine Learning Engineer, you will play a crucial role in planning and developing our machine learning infrastructure, coordinating with the Biology team, and building software that stores and analyzes microscopy data.

Key Responsibilities
  • Develop and implement computer vision and machine learning models to predict cell behavior
  • Lead a team of Machine Learning and Software Engineers in project planning, mentoring, and implementing agile methodology
  • Architect, build, and maintain scalable and distributed machine learning infrastructure, including big data pipelines, large-scale model training, and serving infrastructure
  • Implement and encourage good code practices, including version control, testing, and reproducibility
  • Communicate complex data insights in a clear and actionable way
Requirements
  • 5+ years of experience as a Machine Learning Engineer, including experience working in a top-tier tech or AI-bio company
  • Proven leadership in technical involvement and guidance of a team of ML and software engineers
  • Strong background in computer vision machine learning models and using modern frameworks for deploying these models
  • Hands-on experience in multi-object detection and segmentation techniques
  • Proficient in training and fine-tuning models and implementing continuous learning practices
  • Experience working within a collaborative multi-functional team environment
  • Experience in architecting, building, and maintaining scalable and distributed machine learning infrastructure
  • Excellent communication and leadership skills
Nice to Haves
  • Experience with DevOps practices and MLOps tools (Kubernetes, Apache Airflow)
  • Familiarity with cloud services (GCP particularly relevant) and containerization
  • Experience in supporting/leading MLOps and Data Engineer operations and teams
  • Experience in a biotechnology company or a background in biology is not necessary, but a genuine interest in this area will be beneficial
  • Experience and desire to research relevant scientific publications