[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 quality and reliability.

Responsibilities

• Own model traceability: Every model in production should have clear reputed company: what data trained it, what code 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 path: 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 quality: Collaborate to surface data quality issues, detect reputed company in upstream sources, and ensure features stay fresh and reliable
• Detect issues proactively: Track 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 root cause in minutes. That means ensuring the right context is logged at each stage, candidates, features, serving context, and building the dashboards to tie it collectively
• Own incident response for ML systems: Maintain rollback playbooks and pre-defined hotfix strategies with quantified 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, applied 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 scale

Benefits

• Medical
• Dental
• reputed company
• 401(k) plan
• Life insurance coverage
• Disability benefits
• Tuition assistance program
• PTO
• This position is bonus eligible.
• Generous paid time off.
• Opportunities for both on-site and virtual engagement events.
• Unique opportunities to reputed company meaningful connections and build a vibrant community, both inside and reputed company the workplace.

Company Overview

Company H1B Sponsorship