Description

Key Responsibilities

• Maintain and support machine learning applications running on Windows and Linux servers in on-premises environments.
• Manage, monitor, and troubleshoot Kubernetes clusters hosting deployed ML/data science workloads.
• Support reliable deployment and operation of models in production environments.
• Implement and maintain monitoring and alerting solutions using DataDog to ensure system health and performance.
• Debug and resolve issues in production environments using monitoring tools and operational best practices.
• Automate operational tasks to improve reliability, scalability, and maintainability.
• Ensure best practices in security, performance, and availability for Kubernetes-hosted applications.
• Document system architecture, deployment processes, and troubleshooting guides.
• Collaborate with engineers and stakeholders to ensure smooth operation of production systems.

Required Qualifications

• Proven experience working with Windows and Linux operating systems in production environments.
• Hands-on experience managing on-premises servers, Kubernetes clusters, and Docker containers.
• Strong understanding of Site Reliability Engineering or DevOps practices.
• Familiarity with monitoring and debugging tools, e.g. DataDog.
• Ability to troubleshoot complex issues in distributed systems.
• Experience with CI/CD pipelines for application deployment.
• Familiarity with AWS cloud platforms.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Qualifications

• Experience supporting production machine learning or data science model deployments.
• Basic understanding of Python for operational support or scripting.
• Familiarity with OT/IT data bridging, utilizing Ignition to stream robotics and PLC telemetry into cloud environments or enterprise time-series databases (e.g., InfluxDB, Prometheus, AWS Timestream).
• Familiarity with ML model lifecycle concepts is a plus, but not required

Key Skills

Education

Bachelor's degree