MLOPS Engineer
Full Time
No Travel Required
On-site
70+
Fitment
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Job Details
Skills
- production ML systems AWS
- Kubernetes/EKS
- documented
- partially implemented Realtime‑ML Playground
Summary
Hi,
Hope you are doing well.
Please find the requirement below and let me know if you have any suitable profile
Position: MLOPS Engineer
Location: Sunnyvale, CA (Onsite) – local candidates are preferred
Rate: $70/hr. C2C is also fine.
Job Description:
Required Skills & Experience
- Strong experience with production ML systems, incident management, and on‑call operations.
- Deep hands‑on expertise with AWS, Kubernetes/EKS, and infrastructure‑as‑code.
- Experience executing platform or environment migrations with minimal production risk.
- Familiarity with CI/CD pipelines, observability, and secure service operations.
- Ability to work independently, own deliverables end‑to‑end and leave high‑quality documentation.
Key Responsibilities
Realtime‑ML Operations & Playground Migration (~45%)
- Act as primary on‑call and maintenance owner for the Realtime‑ML production stack during the Auriga migration window.
- Monitor system health, triage and resolve incidents, and address data/model‑serving issues.
- Apply security updates, dependency patches, and ensure SLA continuity for downstream consumers.
- Lead migration of the Realtime‑ML Playground environment, including infra parity checks, configuration migration, integration testing, and documentation.
EKS Migration – HarperCollins Bundles (~40%)
- Execute end‑to‑end migration of HarperCollins service bundles to AWS EKS.
- Author Kubernetes manifests, configure IAM and networking, and update CI/CD pipelines.
- Validate in staging and perform a controlled production cutover.
- Produce rollback plans and operational runbooks.
Buildings Production Pipeline (Supporting, ~15%)
- Contribute to design and initial build‑out of a pipeline streaming ML‑detected missing building into the Basemap data flow.
- Deliver pipeline scaffolding, integration patterns with upstream ML outputs, and schema inputs.
- Leave a documented, partially implemented pipeline with clear handoff notes for post‑engagement completion.
Key Deliverables (by End of Engagement)
- Stable Realtime‑ML production environment throughout Auriga migration, with documented incidents and resolutions.
- Fully migrated Realtime‑ML Playground with handoff documentation.
- HarperCollins bundles live on EKS with completed cutover and operational runbooks.
- Partially implemented Buildings pipeline with documentation enabling seamless handoff.
- All code, IaC, and documentation checked into team repositories.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91173481
- Position Id: 8981404
- Posted 1 day ago
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