Building Intelligent Systems: A Large-Scale Machine Learning Expert

6 days ago

Aurangābad, India beBeeMachineLearning Full time

Large-Scale Machine Learning Systems EngineerWe're seeking a skilled Large-Scale Machine Learning Systems Engineer to build and maintain AI/ML features for an open-source Observability Platform.Design, develop, and operate ML systems in production, collaborating with SREs, service owners, and observability SMEs to ensure scalability and reliability.Develop data pipelines using Databricks and related tools, and apply CI/CD and MLOps best practices to automate model deployment and testing.Maintain and deploy ML infrastructure on AWS or Azure, and set up and integrate MCP servers with observability systems.Troubleshoot ML system performance and reliability issues using OpenTelemetry pipelines and observability metrics.Requirements:Master's degree in Computer Science, Engineering, or Artificial Intelligence, or equivalent experience.Hands-on experience with LLMs/MCPs, Grafana, and Databricks.Strong coding skills in Python, and familiarity with Kubernetes, container orchestration, and cloud platforms (AWS/Azure).Solid understanding of observability pillars (metrics, logs, traces), and experience implementing OpenTelemetry pipelines for ML systems.Knowledge of CI/CD, MLOps, and monitoring best practices.About the Role:This is an exciting opportunity to join our team as a Large-Scale Machine Learning Systems Engineer. We are looking for someone who is passionate about building reliable ML systems and has experience working with LLMs/MCPs, Grafana, and Databricks.What You'll Do:You will be responsible for designing, developing, and operating ML systems in production, collaborating with SREs, service owners, and observability SMEs to ensure scalability and reliability. You will also develop data pipelines using Databricks and related tools, and apply CI/CD and MLOps best practices to automate model deployment and testing.Our Ideal Candidate:We are looking for someone who has a Master's degree in Computer Science, Engineering, or Artificial Intelligence, or equivalent experience. You should have hands-on experience with LLMs/MCPs, Grafana, and Databricks, and strong coding skills in Python. Familiarity with Kubernetes, container orchestration, and cloud platforms (AWS/Azure) is also required.

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