ML Model Architect

12 hours ago

Agra, Uttar Pradesh, India beBeeMachineLearning Full time US$ 1,50,000 - US$ 1,70,000
Senior MLOps Engineer

We are looking for a skilled Senior MLOps Engineer to help us achieve our goals in AI and machine learning.

Key Responsibilities:

  • Productionize models from tracked experiments to governed releases, ensuring resilient services with clear SLOs, runbooks, and fast, safe rollbacks.
  • Build automation-first delivery: reproducible builds, layered tests, and environment promotion via CI/CD pipelines and infrastructure-as-code.
  • Engineer scalable serving: batch and real-time inference on cloud-based platforms and feature stores with probes, autoscaling, and canary/blue-green deployments.
  • Instrument end-to-end observability (data, model, system); detect drift/regressions; lead incidents and post-mortems that drive durable fixes.
  • Partner across teams to translate requirements into designs, architectural decision records, and change plans; balance security, privacy, cost, and performance tradeoffs.
  • Continuously reduce toil through automation, optimize model/GPU/LLM cost, and evolve templates/playbooks for repeatable delivery.

Requirements:

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field and 3+ years of relevant experience as outlined in the essential duties; or High School Diploma/General Education Degree and 6+ years of relevant experience as outlined in the essential duties in lieu of Bachelor's Degree.
  • 3+ years operating ML systems in production (MLOps).
  • Experience with Python for ML engineering (packaging, typing, testing, performance)
  • Experience developing CI/CD pipelines for ML/GenAI (multi-stage workflows, artifacts, evaluation/security gates) and infrastructure-as-code for ML/GenAI (reusable modules, drift detection); secure packaging & containerization.
  • Experience deploying and operating compute for ML (cloud-based platforms), and secure data access patterns (private storage, network isolation, access controls); experience with features stores.
  • Experience implementing MLflow tracking, model registry & governed promotion, packaging & deployment to multi-target runtimes.
  • Experience operating real-time + batch/streaming inference workloads, ML observability, layered testing (unit/integration), workflow orchestration, and cost optimization.
  • Experience designing and implementing least-privilege access, secrets/key management for CI/CD pipelines; privacy and compliance awareness.

Preferred Qualifications:

  • Advanced CI/CD pipeline development (dynamic workflows, components, cross-project triggers, security scans, compliance gates).
  • Advanced infrastructure-as-code development (policy-as-code, gated plan/apply, environment promotion).
  • Advanced real-time serving (multi-tenant routing, dynamic model loading) and SLO-driven rollback/automation.
  • Features store governance (lineage) and feature platform approval/reuse workflows.

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