Location: Remote or HybridEmployment Type: Full-timeAbout ValuematicWe specialize in intelligent autoscaling solutions, leveraging ML-driven time series forecasting and optimization algorithms to predict and manage cloud resource usage dynamically.About the RoleWe are looking for a Data Scientist / ML Engineer with expertise in time series forecasting, optimization algorithms, and ML model deployment. You’ll work on developing predictive models that anticipate cloud workload demands and optimize resource allocation.Your Responsibilities:Develop time series forecasting models for autoscaling predictionsBuild algorithms for dynamic resource allocationDesign and deploy scalable ML pipelines for real-time cloud managementImplement MLOps strategies for continuous model monitoring and retrainingWork with large-scale data streams to drive automation and insightsWhat You BringExpertise in time series modeling and forecasting techniquesStrong Python skills with experience in ML frameworksExperience in reinforcement learning and optimization methodsFamiliarity with containerization and cloud-native ML deploymentKnowledge of real-time data processing and streaming architecturesCompetitive salary and performance-based incentivesRemote-first work environment with flexible hoursOpportunity to work on technically challenging problems in cloud infrastructureDirect impact on product direction and technical strategyA fast-paced, no-bureaucracy startup cultureWhy Join Valuematic?Build AI-driven autoscaling solutions for global cloud providersWork on real-time, high-impact optimization challengesBe part of an innovative start-up defining the future of cloud computingSend us your GitHub/GitLab profile or a few notes about what projects you’ve built or managed. We care more about hands-on experience and problem-solving than perfect resumes.Contact
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