We are hiring for a company utilizing behavioral data to develop Personal Healthcare Agents by combining sensor-based technologies with natural language processing. Their team consists of committed digital health researchers, machine learning experts, and clinicians from leading institutions in academia and industry.
What You Will Be Doing
As the Lead Machine Learning Engineer, you will be responsible for guiding a team in creating and implementing computer vision and machine learning models to predict cell behavior. Your role will involve developing and deploying these models, as part of optimizing human tissue manufacturing for research and therapeutic applications. Additionally, you will play a key role in planning and developing the machine learning infrastructure. Collaboration with the Biology team, who conduct cell biology experiments and collect microscopy data, will be essential.
Qualities/Skills that the Company Hiring is Looking For
5+ years of experience as a Machine Learning Engineer, with a focus on transitioning models from concept to production.
Proven leadership in guiding technical teams
Experience in MLOps and Data Engineer operations
Strong background in computer vision ML models
Proficiency in Python, PyTorch, and TensorFlow
Skilled in cloud services, containerization, and distributed systems
Experience in architecting scalable ML infrastructure
Excellent communication skills for conveying complex data insights
Desirable Things the Company Hiring is Looking For
Experience with DevOps practices and MLOps tools like Kubernetes and Apache Airflow.
A genuine interest in biotechnology or biology
A desire to research scientific publications is desirable.
What the Company Hiring is Offering
Join a rapidly growing technology company at the forefront of artificial intelligence and stem cell biology. Benefit from a dynamic, inclusive, and collaborative culture focused on impactful health solutions. Enjoy a competitive salary, founding equity compensation, and the opportunity to work in a hybrid setting or at the Bristol, UK headquarters. Participate in bi-annual week-long company off-sites.