As a Software Engineer on the Infrastructure team, you'll accelerate the Snorkel AI team and our customers by improving our developer platform and services for user and data management across the stack. You’ll work closely with other engineers, researchers, and product management to align on the highest leverage improvements for CI/CD, cloud infrastructure, deployment, security, authentication/authorization, and more.
Main Responsibilities
- Design, build, and maintain services and deployment for Snorkel’s enterprise platforms
- Design, build, and improve observability and alerting for Snorkel’s enterprise platforms
- Contribute to Snorkel’s in-house fleet management software for installation and upgrades of deployments for Snorkel’s enterprise customers
- Build and improve Snorkel’s production and staging infrastructure; own our k8s and cloud strategy
- Work closely with various engineering teams in defining test strategies and build infrastructure to execute the same
- Deploy and optimize CI/CD pipelines across multiple environments and continuously improve development and deployment best practices
- Collaborate with enterprise customers to understand product use cases and translate into engineering specifications, and deliver high-quality solutions
- Participate in on-call responsibilities in rotation with the engineering team
- Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office
Minimum Qualifications
- Bachelor's degree in Computer Science or related field, or equivalent demonstrated experience
- Strong development and debugging skills in Python
- 3+ years of experience in software development (including academic experience)
- Understanding of Kubernetes ecosystem
Preferred Skills
- Extremely well versed in building and managing cloud infrastructure for enterprise platforms on (AWS, GCP, Azure) and services like EC2, EKS, VPC etc
- Experience in one or more of the build tools like Bazel, Gradle, Make etc.
- Familiarity in developing and releasing infrastructure software for SaaS products
- [Nice to have]: Hands on experience in CI/CD and test infrastructure for very large and complex code bases
- [Nice to have]:Experience with large scale distributed computing systems for ML Training or Serving, eg: Ray, Spark, Tensorflow etc
- [Nice to have]:Hands-on experience in creating and maintaining metrics and dashboards on observability platforms such as New Relic, DataDog, Chronosphere, or similar tools
- [Nice to have]:Experience building services and infrastructure for Machine learning and AI Systems
The salary range for this position based in the San Francisco Bay Area is $200,000.00 - $230,000.00. All offers include equity compensation in the form of employee stock options.
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