Staff Software Engineer, Snorkel AI
Infrastructure
$220-275k
+ offers include equity compensation in the form of employee stock options
3 days a week in office
Data-centric enterprise AI platform for
Be an early applicant
Data-centric enterprise AI platform for
101-200 employees
Be an early applicant
$220-275k
+ offers include equity compensation in the form of employee stock options
3 days a week in office
101-200 employees
Company mission
To empower everyone to solve their most impactful problems through data-centric AI.
Role
Who you are
- Bachelor's degree in Computer Science or related field, or equivalent demonstrated experience
- 8+ years of experience in distributed systems and cloud-native applications
- Strong experience with cloud platforms and infrastructure as code (Terraform, CloudFormation, Helm)
- Deep expertise building services on Kubernetes (EKS, GKE etc)
- Regularly follows the best software engineering practices and hold a high bar for the team by leading design, code review and test plan reviews
- Proven ability to lead and mentor teams of engineers
Desirable
- Strong development experience in Python or other language like Java, golang, scala etc
- 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. Extra points for someone who has hands on experience in building and managing large code bases with these tools
- Designed and implemented developer-friendly APIs or tools to boost developer productivity
- Familiarity in deployment, monitoring and maintenance of large-scale enterprise software products
- Follow the best software development practices, and hold the high engineering bar for the team by regularly leading design, code review and test plan reviews
- Experience working cross-functionally across teams including product, design, customer success and support
- Familiarity in developing and releasing infrastructure software for SaaS and on-prem platforms
- Have a voracious and intrinsic desire to learn and fill in missing skills—and an equally strong talent for sharing learnings clearly and concisely with others
- [Nice to have]: Hands-on experience setting up and operating Kubernetes clusters in production at scale
- [Nice to have]: Experience leading teams building 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
What the job involves
- 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
- Deploy and maintain CI/CD and software release pipelines across multiple environments and continuously improve testing frameworks development tooling and deployment best practices
- Define and build our deployment strategy, internal and external, for SaaS-hosted, on prem, and managed service offerings
- Build and maintain Snorkel’s production and staging infrastructure, own our k8s and cloud strategy
- Design, develop, and maintain observability, alarms, and monitoring tools
- 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 and work remotely with "No Meeting" Tuesdays and Thursdays
Our take
Demand for AI is increasing in almost every industry, but the machine learning that fuels it is tedious to set up. In order to train machine learning algorithms, training data must be labelled manually, and this contributes to expenses in time, money and resources when integrating AI within a business.
Snorkel AI develops programmatic approaches to data labelling in order to automate the setup process of machine learning and decrease the required timeframe for a business to begin providing AI services. In addition to these automated data categorization services, the company also integrates data training, management, and analysis into a unified AI-deployment platform.
The complex computer science behind AI setup has resulted in many businesses without computer science backgrounds being left behind, and Snorkel AI has set this as their target audience. As of 2023, this customer base has tripled in size since Snorkel AI's founding and in 2024, enjoyed a new round of funding. With these promising developments, the company continues to innovate the sector.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Aug 2021
$85m
SERIES C
Apr 2021
$35m
SERIES B
Total funding: $135m
Company benefits
- Home office allowance
- Yearly wellness stipend
- Healthy meals, snacks & drinks in office
- 401k with a 100% match up to 5% of annual salary
- Regular team events
- Generous paid parental leave
- Work from home opportunities
- Health insurance
Company HQ
Centennial, Redwood City, CA
Leadership
Alex Ratner
(Co-founder & CEO)Studied at Harvard and received a PhD from Stanford. They are also an Assistant Professor at the University of Washington.
Paroma Varma
(Co-founder)They hold a PhD from Stanford and was VP of Corporate Relations at the Society of Women Engineers. They have collaborated with teams at Facebook and Intel.
Braden Hancock
(Co-founder & Head of Technology)They have a PhD in Computer Science from Stanford, and worked as a Research Assistant with the Air Force and MIT. They were also a Software Engineer at Google, and a Researcher at Facebook.
Henry Ehrenberg
(Co-Founder)They studied at Yale and Stanford and worked at Facebook as a Quantitative Engineering Intern and a Senior Applied Research Scientist.
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