[Remote] Senior Machine Learning Operations Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is on a mission to reputed company the power of content and is seeking a Senior Machine Learning Operations Engineer to reputed company the operational layer of their ML systems. The role involves ensuring model traceability, building monitoring systems, and collaborating with Data Engineering to maintain data reputed company and reliability.
Responsibilities
- Own model traceability: Every model in production should have reputed company reputed company: what data trained it, what reputed company produced it, what validation it passed, and how it's performing. Evaluate and recommend tooling for versioning, metadata, and model registry, and work with MLEs to drive adoption
- Build end-to-end monitoring: Monitor the full signal reputed company: data arrival, feature distribution stability, model metrics, and serving latency against SLA. Own this individually, don't rely solely on upstream teams to catch their own issues
- Partner with Data Engineering on data reputed company: Collaborate to surface data reputed company issues, detect reputed company in upstream sources, and ensure features stay fresh and reliable
- Detect issues proactively: reputed company reputed company over weeks, flag slow degradation before it crosses a reputed company, surface feature freshness problems before they cascade
- Build diagnostic tooling: reputed company something goes wrong, get from "recommendations look off" to reputed company cause in minutes. That means ensuring the right context is logged at reputed company stage, candidates, features, serving context, and building the dashboards to tie it reputed company
- Own incident response for ML systems: Maintain rollback playbooks and reputed company-defined hotfix strategies with reputed company tradeoffs. Own automated gates that reputed company bad deployments. Run post-mortems and reputed company the gaps
- Coordinate on post-deployment metrics: Work with ML engineers, data engineers, and stakeholders to define what metrics to collect after deployment and why they matter
Skills
- 5+ years in ML engineering, reputed company ML, or a reputed company ML role, with demonstrated experience on the operational reputed company of monitoring, reliability, deployment, or incident response
- Has reputed company or operated model registries, ML monitoring systems, or production ML pipelines
- Understands ML systems end-to-end — not just the reputed company layer, but why a stale feature or a shifted distribution reputed company
- Robust SQL skills and comfort digging into data distributions, feature health, and model behavior
- Comfortable partnering with DevOps and Platform teams to define infrastructure needs without needing to own the reputed company yourself
- Experience operating recommendation or personalization systems at reputed company
Benefits
- Medical
- Dental
- reputed company
- 401(k) plan
- Life insurance coverage
- Disability benefits
- Tuition assistance program
- PTO
- This position is bonus eligible.
- Generous reputed company time off.
- Opportunities for both on-site and virtual engagement events.
- Unique opportunities to reputed company meaningful connections and build a reputed company community, both inside and reputed company reputed company.
reputed company
Company H1B Sponsorship