Senior Infrastructure Engineer

Freenome is hiring an experienced infrastructure engineer to help build a cloud-native machine learning platform for the world’s largest multi-analyte cancer genomics dataset.

As an engineering-forward biotech company, we apply modern engineering practices to build reliable, maintainable, scalable, and secure production systems for our clinical lab and Computational and Molecular Research Scientists.

Our infrastructure team is a small group where you will help set the culture and build the systems that allow us to move fast without breaking things. This is an opportunity to do meaningful engineering work that will directly save lives.

We value:
Rapid iteration and tight feedback loops
Continual improvement rather than disruption
Technical simplicity and elegance
A focus on the larger goals
Mutual respect and blameless postmortems
A culture of diversity and inclusion

Responsibilities include:
Improving the reliability and scalability of our platform for genomic research in concert with the Software Engineers and Computational Scientists who depend on it daily
Planning for significant growth and scaling challenges as we transition from research to product development
Lending your expertise to design and code reviews
Anticipating technical scaling limits before we reach them
Continually improving our security posture
Reinforcing good development practices across the entire organization

What We're Looking For:
5+ years of experience with production infrastructure, automation, and monitoring
B.S. or M.S. in computer science or a related technical field, or comparable experience
Experience in analyzing and troubleshooting distributed systems
Software design and development expertise, especially in Python
Practical knowledge of Linux internals
A systematic problem-solving approach, coupled with effective communication skills and a sense of ownership and drive

Nice to Haves:
Machine learning and data science tools, such as TensorFlow, PyTorch, Jupyter, or Kubeflow
Systems programming languages such as Go, Rust, or modern C++
Kubernetes, including tools such as Helm or Flux
Docker and Linux containers
Production deployment automation tools, such as Terraform or Ansible
Large-scale and/or high-performance storage systems, such as PostgreSQL, MySQL, Redis, HBase, Spanner, or Cassandra
Microservices, service meshes, or distributed tracing
Security, encryption, and certificate management
Networking, firewalls, load balancers, and HTTP internals
Monitoring, alerting, logging, and tracing tools, such as Prometheus, fluentd, or Jaeger
Data pipelines, such as Kafka, Spark, Airflow, Argo, Beam, or Flink
Google Cloud Platform experience
Experience with software in a regulated environment
Genomics or bioinformatics background