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3110 K-T India
AI/ML Engineer - MLOps/SRE
3110 K-T India
Chennai•On-site•5-8 Yrs•Jun 21
Job description
Overview
Company Overview KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem.
Responsibilities
- Design and implement reusable MLOps platform capabilities for training, deployment, and monitoring of ML/LLM systems.
- Build standardized pipelines for data validation, feature generation, training, evaluation, model packaging, and release. Own model registry, artifact storage, and metadata lineage to ensure reproducibility and auditability. Deployment Engineering & Release Safety
- Deploy models and AI services using containers and orchestration (e.g., Kubernetes) with robust rollout strategies (blue/green, canary, A/B).
- Create CI/CD workflows for ML code and pipelines, including automated tests, quality gates, and approval controls. Harden inference services for low latency and high throughput using caching, batching, autoscaling, and efficient model serving patterns. Reliability, Observability & Incident Response (SRE) Define and track service-level indicators (SLIs) and service-level objectives (SLOs) for ML services, pipelines, and data dependencies.
- Implement end-to-end observability: structured logging, metrics, tracing, dashboards, and alerting for both infrastructure and model behavior.
- Lead incident response and post-incident reviews; drive systemic fixes through runbooks, automation, and reliability engineering practices. Model & Data Monitoring
- Implement monitoring for model quality and data health: drift, bias, performance degradation, and data pipeline anomalies.
- Build automated feedback loops to trigger investigations, retraining workflows, and safe rollback when quality thresholds are breached. Security, Compliance & Governance
- Integrate security best practices: secrets management, least-privilege access (RBAC), network controls, and vulnerability scanning.
- Support compliance and governance requirements for model usage, data access, retention, and responsible AI practices. Collaboration & Enablement Partner with data science and engineering teams to translate business requirements into reliable, scalable ML solutions.
Qualifications
- of 3 years;
- Bachelor's Level Degree and related