Tahoe Therapeutics is pioneering a new approach to drug discovery using in vivo data generation and machine learning to find better drugs faster. The company needs to build and maintain the cloud and software infrastructure to support its large-scale data pipelines and machine-learning platform.
Requirements
- Deep familiarity with cloud platforms (AWS preferred), containers (Docker), and Kubernetes.
- Solid Python programming skills.
- Familiarity with Linux based operating systems.
- Proven track record designing scalable, cloud-native architectures and data services.
- Prior exposure to ML-ops or MLOps support workflows.
- Exposure to large-scale genomics data.
- Exposure to computational chemistry applications.
Responsibilities
- design, build and help maintain the cloud and software infrastructure that underpins both our large-scale data pipelines and state-of-the-art machine-learning platform.
- proactively identify the organization software needs by partnering closely with experimental and computational scientists.
- champion best practices around scalability, documentation, cost optimization and security.
- Partner with data engineers, ML scientists, and experimental biology teams to translate scientific requirements into robust technical solutions.
- Lead design and implementation of scalable, secure, cost-efficient infrastructure (compute, storage, networking, and orchestration) on AWS.
- Mentor and uplift the engineering organization through architecture reviews, design patterns, and technical documentation.
Other
- This role requires physical presence in the South San Francisco office for at least 3 days per week.
- Experience partnering with cross-disciplinary stakeholders to define and deliver software solutions.
- Prior experience working in health care, life sciences or other regulated industries.
- We welcome applications from candidates in both Toronto, ON or San Francisco, CA, regions or those willing to relocate to the Bay Area or the Greater Toronto Area.
