MLOps Engineer_4+YRS

2 days ago

Hyderabad, Telangana, India Zorba AI Full time ₹ 8,00,000 - ₹ 24,00,000 per year

MLOps Engineer

Industry & Sector:
Enterprise software and AI services delivering production-grade machine learning solutions, model lifecycle automation, and cloud-native data engineering for commercial clients. We build scalable, secure ML platforms that power analytics, recommendation, and prediction services.

Location & Work Type:
India — On-site role

About The Opportunity
We are hiring an experienced MLOps Engineer to join a consulting-led technology practice that implements end-to-end ML platforms and production ML systems for enterprise clients. You will work closely with data scientists, backend engineers, and cloud architects to operationalize models, automate ML pipelines, and ensure reliable, observable model serving at scale. This position reports to the platform engineering lead at Zorba Consulting India and requires on-site presence in India.

Role & Responsibilities-

  • Design multi-agent architectures: define agent roles (planner, researcher, retriever, executor, reviewer), toolboxes, handoffs, memory strategy (short/long-term), and supervisor policies for safe collaboration.
  • Build high-quality RAG: implement ingestion, chunking, embeddings, indexing, and retrieval with evaluation (precision/recall, groundedness, hallucination checks), guardrails, and citations.
  • Productionize on AWS: leverage services like Bedrock (Agents/Knowledge Bases/Flows), Lambda, API Gateway, S3, DynamoDB, OpenSearch/Vector DB, Step Functions, and CloudWatch for tracing and alerts.
  • MLOps/LLMOps: automate CI/CD (GitOps), containerization (Docker/Kubernetes), infra-as-code, secrets/IAM, blue green/rollbacks, and data/feature pipelines.
  • Observability & evaluation: instrument telemetry (traces, token/cost, latency), build dashboards (Grafana/CloudWatch), add human-in-the-loop review, A/B testing, and continuous offline/online evals.
  • Operate reliably at scale: implement caching, rate-limit management, queueing, idempotency, and backoff; proactively detect drift and degradation.
  • Collaborate & communicate partner with infra/DevOps/data/architecture teams; document designs, SLIs/SLOs, runbooks; present status and insights to technical and non-technical stakeholders.

Skills: python,kubernetes,docker,aws,terraform

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