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
How you’ll contribute:
- 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 you’ll bring:
- 8+ 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