Data-Driven Machine Learning Solutions Specialist

2 days ago


salem, India beBeeMachineLearning Full time

About This PositionWe are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have expertise in designing, developing, and operating machine learning systems in production environments.ResponsibilitiesDesign and Develop AI-Powered Observability Platform: Create an open-source observability platform that incorporates AI capabilities for enhanced insights across enterprise settings.Collaborate with SREs and Observability Experts: Work closely with software reliability engineers and observability subject matter experts to ensure the scalability and reliability of ML model deployments.Develop Data Pipelines Using Databricks: Design and implement data pipelines using Databricks and related tools to support business needs.Implement CI/CD and MLOps Best Practices: Automate model deployment and testing processes by implementing industry-standard CI/CD and MLOps best practices.Deploy and Manage ML Infrastructure on Cloud Platforms: Deploy and manage machine learning infrastructure on cloud platforms, ensuring seamless operation and high performance.Troubleshoot ML System Performance: Identify and resolve issues affecting the performance and reliability of machine learning systems using OpenTelemetry pipelines and observability metrics.RequirementsMaster's Degree in Computer Science or Related Field: Possess a master's degree in computer science, engineering, or artificial intelligence.Proven Experience in ML Systems Development: Have a proven track record of designing, developing, and operating machine learning systems in production environments.Familiarity with LLMs/MCPs, Grafana, and Databricks: Be familiar with large language models, model checkpoints, Grafana, and Databricks.Strong Coding Skills in Python: Possess strong coding skills in Python, a popular programming language for machine learning applications.Familiarity with Kubernetes, Container Orchestration, and Cloud Platforms: Be familiar with container orchestration using Kubernetes and cloud platforms for scalable and efficient operations.Solid Understanding of Observability Pillars: Have a solid understanding of the three pillars of observability: metrics, logs, and traces.Experience Implementing OpenTelemetry Pipelines: Have experience implementing OpenTelemetry pipelines for machine learning systems to enhance observability and reduce debugging complexity.About UsWe offer a dynamic work environment that fosters innovation and collaboration. Our team is passionate about leveraging machine learning to drive business growth and improvement. We're committed to supporting your professional development and providing opportunities for growth and advancement.



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