ashby
Staff ML Ops Engineer
LiveView Technologies
Seattle, USA
Full-time
Senior · 8+ years experience
Onsite
USD 213300-272000 yearly / year
Discovered 1 weeks ago
KubernetesArgoNVIDIA JetsonLangGraphMCPvector databases
Free
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Role Overview
We are seeking a Staff ML Ops Engineer to own the model lifecycle as infrastructure that turns the path from research to production into standardized self-serve tooling.
The model portfolio this platform serves spans both the computer-vision models in production today and a growing set of LLM, VLM, and agentic workloads.
Bringing those generative workloads under the same lifecycle discipline: serving, version-pinning, evaluation, guardrails, and cost and latency monitoring is a part of this role's scope.
This is a senior individual-contributor and technical-leadership role.
You will partner closely with AI/ML research, the application backend team, and platform and infrastructure teams.
You should be equally comfortable discussing model-serving architectures, CI/CD and rollback design, polyglot service contracts, and production observability.
Key Skills for This Role
KubernetesArgoNVIDIA JetsonLangGraphMCPvector databases
Full Job Posting
ABOUT THIS ROLE
We are seeking a Staff ML Ops Engineer to own the model lifecycle as infrastructure that turns the path from research to production into standardized self-serve tooling. The model portfolio this platform serves spans both the computer-vision models in production today and a growing set of LLM, VLM, and agentic workloads. Bringing those generative workloads under the same lifecycle discipline: serving, version-pinning, evaluation, guardrails, and cost and latency monitoring is a part of this role's scope.
This is a senior individual-contributor and technical-leadership role. You will partner closely with AI/ML research, the application backend team, and platform and infrastructure teams. You should be equally comfortable discussing model-serving architectures, CI/CD and rollback design, polyglot service contracts, and production observability.
ROLE RESPONSIBILITIES
- MLOps: Own the model lifecycle end to end: standardized packaging, a model CI/CD path, a serving layer with stable, versioned contracts, automated deployment and rollback, and monitoring and drift detection.
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