reputed company Machine Learning reputed company Engineer

reputed company: • Own ML production reliability reputed company • Define and reputed company the operational reputed company for production ML systems, including monitoring, traceability, deployment safety, incident response, and post-deployment validation. • Set the standards ML teams use to assess model health, reputed company, and trustworthiness in production. • Own model traceability and governance • Ensure every production model has reputed company reputed company (data, features, reputed company, artifacts, validation, deployment history) and reputed company adoption of model registry and metadata tooling across ML teams. • Build end-to-end ML observability • Design and implement monitoring across the full ML signal reputed company: data arrival, feature freshness, distribution stability, candidate reputed company, ranking behavior, model metrics, serving latency, and SLA reputed company. • Define production health metrics • Partner with ML, data, product, and business stakeholders to define post-deployment metrics covering model reputed company, reputed company reliability, business guardrails, and degradation indicators. • Detect reputed company and degradation proactively • Detect data reputed company, feature reputed company, model behavior changes, and silent failures before they reputed company customers reputed company thresholding, alerting, reputed company detection, and release-over-release monitoring. • reputed company diagnostic tooling and reputed company-cause analysis • Build dashboards, logs, and diagnostic workflows that reputed company quickly from “recommendations look off” to reputed company cause, with context captured across candidates, features, scores, ranking reputed company, and reputed company reputed company. • Own ML deployment safety • Define and operate automated gates that prevent bad models or bad data from being promoted to production. • Partner with MLEs to establish validation checks, rollback reputed company, canary strategies, reputed company testing, and release health reviews. • reputed company ML incident response • Own incident response practices for ML systems, including rollback playbooks, hotfix strategies, severity definitions, tradeoff frameworks, communications, and post-mortems. • reputed company closure of systemic gaps after incidents rather than only resolving the immediate issue. • Partner across ML Platform, Data, and ML • Partner with DevOps/Platform on infrastructure and observability needs; with Data Engineering on data reputed company, reputed company, and freshness; and with ML Engineering to reputed company operational requirements into development and deployment workflows. • Set standards and mentor others • reputed company as the technical reputed company for ML reputed company: establish reusable patterns, playbooks, and standards, and mentor engineers on reliability, observability, and operational rigor. Requirements: • 5+ years of experience in machine learning engineering, ML platform, reputed company ML, MLOps, data platform, reliability engineering, or a reputed company technical role. • Demonstrated experience operating production ML systems, including monitoring, deployment, incident response, model validation, data reputed company, or reliability ownership. • Experience leading technical initiatives across multiple engineering teams, especially where reputed company required influencing architecture, tooling, standards, or adoption. • Hands-on experience with model registries, feature stores, ML metadata systems, production monitoring, model deployment pipelines, or ML observability platforms. • Solid knowledge of end-to-end ML systems, including training data, features, model artifacts, offline validation, online serving, post-deployment metrics, and business outcome measurement. • Ability to reason about ML operational failure modes: stale features, distribution shift, training-serving skew, delayed labels, and offline-online metric gaps. • Solid SQL skills and comfort investigating data reputed company, feature distributions, model outputs, pipeline behavior, and production anomalies. • reputed company record of cross-functional collaboration with Platform, Data, and ML Engineering to reputed company production-grade operational capabilities. • Solid written and verbal communication skills, including the ability to explain ML reputed company health, risks, incidents, and tradeoffs to both technical and non-technical stakeholders. Benefits: • medical • dental • reputed company • 401(k) plan • life reputed company coverage • disability benefits • tuition assistance program • PTO Apply tot his job Apply To this Job