Building Scalable ML Systems Architect

3 days ago

vellore, India beBeeMachineLearning Full time

Observability Platform Engineer OpportunityWe are seeking a skilled Machine Learning Observability Platform Engineer to join our team. The ideal candidate will be passionate about building scalable and reliable ML systems.Develop and maintain AI/ML features for an open-source observability platform built on Grafana and ClickHouse.Collaborate with SREs, service owners, and observability experts to ensure the deployment of ML models is seamless and efficient.Design and manage data pipelines using Databricks and related tools to extract valuable insights from complex data sets.Implement CI/CD and MLOps best practices to automate model deployment and testing, ensuring high-quality and robust ML systems.Deploy and manage ML infrastructure on cloud platforms like AWS or Azure.Set up and integrate MCP servers and connect tools across observability systems to provide real-time insights.Establish standards for promptness and develop custom MCP integrations between systems.Troubleshoot ML system performance and reliability using OpenTelemetry pipelines and observability metrics.RequirementsMasters degree in Computer Science, Engineering, or Artificial Intelligence (or equivalent experience).Proven experience designing, developing, and operating ML systems in production environments.Hands-on experience with LLMs/MCPs, Grafana, and Databricks.Strong coding skills in Python programming language.Familiarity with Kubernetes, container orchestration, and cloud platforms (AWS/Azure).Solid understanding of observability pillars (metrics, logs, traces).Experience implementing OpenTelemetry pipelines for ML systems.Knowledge of CI/CD, MLOps, and monitoring best practices.

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