Platform Engineering Leader: Scale, Reliability & On‑Prem

Reducto; San Francisco (CA); On-site; USD 230,000 - 320,000; Full time

Benefits offered by this job

Unlimited PTO

Free lunch

Transportation reimbursement

Health insurance

Wellness budget

Parental leave

Job summary

Reducto is hiring a Head of Platform Engineering in SF to own the platform end to end, from job orchestration to model inference, with hands-on coding and leadership. You will shape the reliability and performance at scale, lead the team, and collaborate with ML and product groups to roll out new capacities.

This in-person role at our SF office requires shipping quickly in a startup environment while building robust production-grade systems.

Qualifications

• 3+ years owning reliability and performance for a large-scale platform.
• Hands-on in design docs, coding, and code reviews.
• Proven track record in attracting and retaining top engineering talent.
• Thrives in fast-moving, ambiguous environments and can lead greenfield work.

Responsibilities

• Own the serving platform end to end, including orchestration, pre/post processing, model inference, autoscaling, and migrations.
• Design and deploy Reducto to customer clouds and on-prem environments.
• Build observability and drive incident response, latency and cost metrics.
• Own the platform roadmap and recruit the platform engineering team.
• Collaborate with Product, ML, and Product Engineering to scale runtimes and environments.
• Develop the internal data platform and support internal users and customers.
• Work closely with ML and Product teams to roll out models and deployment capabilities.

Skills

Reliability ownership

Hands-on coding

Hiring experience

Ambiguity handling

Platform engineering

Infrastructure as Code

Container deployments

Tools

Terraform

Kubernetes

Docker

Job description

Reducto is hiring a Head of Platform Engineering in SF to own the platform end to end, from job orchestration to model inference, with hands-on coding and leadership. You will shape the reliability and performance at scale, lead the team, and collaborate with ML and product groups to roll out new capacities.

This in-person role at our SF office requires shipping quickly in a startup environment while building robust production-grade systems.