Machine Learning Infrastructure Specialist
Há 5 horas
Unlock the Power of MLOps EngineeringWe're on a mission to revolutionize our machine learning infrastructure, and we need your expertise as an MLOps Engineer.As a key member of our team, you'll play a vital role in bridging the gap between data science and operations.You'll design, automate, and optimize our ML workflows from experimentation to production, ensuring scalability, high availability, and performance.Key Responsibilities:Design and build end-to-end machine learning infrastructure using best practices and industry standards.Automate ML pipelines with Docker, Kubernetes, and CI/CD frameworks for seamless deployment and monitoring.Collaborate closely with data scientists and engineers to streamline model deployment and ensure seamless integration with existing systems.Monitor and optimize models in production using observability tools like Prometheus, Grafana, and ELK.Manage and optimize cloud infrastructure for efficiency and cost-effectiveness.Ensure compliance and security protocols are met for sensitive financial data.Provide expert support and maintenance to ensure the reliability and performance of ML applications.Requirements:Proven experience as an MLOps Engineer or similar role in fintech or AI startup environments.Strong programming skills in Python (or Java/Scala) with hands-on experience with ML frameworks and pipeline orchestration (e.g., MLflow, Airflow, Kubeflow).Experience with cloud services (AWS, Azure, or GCP) and containerization/orchestration (Docker, Kubernetes).Familiarity with Git and CI/CD tools, with a strong understanding of ML algorithms and their real-world applications.Excellent communication and collaboration skills, with the ability to work effectively in a remote, cross-timezone team environment.Bachelors or Masters degree in Computer Science, Data Science, or related field (or equivalent experience).
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