Responsibilities:

• Package models, deploy to production environments, and monitor usage and performance.
• Design, implement, and deploy ways to make complex deep learning models usable by biologists and other domain specialists.
• Manage ML infrastructure, both on premises and in the cloud.
• Rapidly prototype POCs in partnership with ML scientists and other stakeholders.
• Test models at scale and ensure CI/CD best practices are followed by the whole team.

REQUIREMENTS

• 3+ years experience in production ML systems, model deployment.
• Proficiency in Kubernetes, cloud technologies (AWS/Azure/GCP) and managing on-prem GPUs.
• Background in distributed systems, containerization, CI/CD.
• Self-motivated problem solver with excellent communication skills.

Nice to have:

• Previous startup experience bringing ML prototypes to production.
• Familiarity with bioinformatics data/pipelinesKnowledge of MLFlow, Kubeflow, Ray, Dask, Fluidstack, or similar tools.

What we offer:

• The opportunity to transform drug discovery through AI.
• A competitive salary plus equity compensation (ESOPs).A wide array of company-paid benefits.
• Flexibility in remote working.
• Exceptional opportunities for learning and growth in a world-class team of researchers and software developers, working at the intersection of the most exciting areas of science and technology.