The role, as published
About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Take ownership of a backend platform that handles high-volume processing workloads, with a focus on speed, dependability and cost control. Collaborate with machine learning colleagues to get models running in production, and share on-call duties within a small platform group.
What you'll do
- Own and improve the backbone platform that executes customer workloads, keeping it quick, dependable and economical as demand grows.
- Collaborate with machine learning engineers on hosting proprietary models efficiently and fitting them into live data pipelines.
- Build and maintain core infrastructure, including data stores, job coordination, resource allocation and cloud releases.
- Resolve performance, resilience and capacity problems across multi-service systems as traffic increases.
- Join the on-call rotation and take responsibility for the overall health of the platform.
What we're looking for
- 5+ years of experience owning and scaling core infrastructure at a fast-paced startup or a respected, high-velocity technology company.
- If coming from a larger company, a Staff or Principal title or a clear record of fast promotion.
- Full-stack skills; this is not a pure infrastructure or DevOps position.
- Solid background building reliable, large-scale backend systems that coordinate work across many services.
- Strong Python skills, or deep experience in another systems language along with willingness to move to Python.
- Comfort taking part in on-call duties.
Bonus points
- Experience with cloud infrastructure and tuning how models are served.
- Experience at an early-stage startup.
- A degree from a top computer science program.
Benefits
- Health, dental and vision coverage
- Parental leave
- Wellness benefits
Location and work model
- San Francisco, CA, United States
- On-site, 5 days per week in office
- Full-time
Compensation, as the posting describes it
- Equity
- Flexible time off