Role Summary We are seeking a highly skilled MLOps Engineer to focus on the deployment, monitoring, and maintenance of machine learning models in production environments. This role is platform-focused and does not involve model development or end-user support. The successful candidate will ensure reliability, scalability, and performance of ML platforms while managing API endpoints and deployment workflows. Key Responsibilities Platform Operations & Monitoring Monitor ML model endpoints and platform health using tools such as Grafana and Domino Data Lab Respond to incidents and alerts; perform code fixes and manage changes via ServiceNow Liaise with Domino Data Lab support to resolve platform-related issues Model Deployment Deploy and maintain ML models in production environments Ensure models integrate seamlessly into automated pipelines Maintain reliability, version control, and governance standards Pipeline Maintenance Collaborate with Data Scientists and Engineers for smooth production handoff Maintain and optimize ML pipelines for stability and scalability Improve performance, resource usage, and automation Automation & Tooling Implement automation for deployment and monitoring Contribute to continuous platform improvements Required Skills & Experience Strong Python programming experience Proven experience deploying and monitoring ML models in production Understanding of model evaluation metrics, data drift, overfitting, and feature importance Experience with AWS services (S3, Redshift, etc.) Hands-on experience with Grafana for monitoring Familiarity with Domino Data Lab (desirable) Strong knowledge of CI/CD, version control, Docker, Kubernetes Excellent troubleshooting and incident management skills Strong stakeholder communication skills
03/03/2026
Contractor
Role Summary We are seeking a highly skilled MLOps Engineer to focus on the deployment, monitoring, and maintenance of machine learning models in production environments. This role is platform-focused and does not involve model development or end-user support. The successful candidate will ensure reliability, scalability, and performance of ML platforms while managing API endpoints and deployment workflows. Key Responsibilities Platform Operations & Monitoring Monitor ML model endpoints and platform health using tools such as Grafana and Domino Data Lab Respond to incidents and alerts; perform code fixes and manage changes via ServiceNow Liaise with Domino Data Lab support to resolve platform-related issues Model Deployment Deploy and maintain ML models in production environments Ensure models integrate seamlessly into automated pipelines Maintain reliability, version control, and governance standards Pipeline Maintenance Collaborate with Data Scientists and Engineers for smooth production handoff Maintain and optimize ML pipelines for stability and scalability Improve performance, resource usage, and automation Automation & Tooling Implement automation for deployment and monitoring Contribute to continuous platform improvements Required Skills & Experience Strong Python programming experience Proven experience deploying and monitoring ML models in production Understanding of model evaluation metrics, data drift, overfitting, and feature importance Experience with AWS services (S3, Redshift, etc.) Hands-on experience with Grafana for monitoring Familiarity with Domino Data Lab (desirable) Strong knowledge of CI/CD, version control, Docker, Kubernetes Excellent troubleshooting and incident management skills Strong stakeholder communication skills
Senior Guidewire ClaimCenter Developer 6+ years' experience with ClaimCenter, Guidewire Certified. Strong in Gosu, Java, SOAP/REST, Studio, Messaging, Data Model, Rules & Workflows. Lead development, integrations, mentoring, code reviews, and performance optimization. Agile/Scrum experience with solid problem-solving and communication skills. Guidewire ClaimCenter Business Specialist/Analyst 5+ years' experience with ClaimCenter, Guidewire Certified (preferred). Skilled in requirements gathering, functional specs, user stories, workshops, and solution validation. Strong in configuration, integrations, data mapping, UAT, and end-user training. Knowledge of insurance regulations, Agile (Jira), and SQL for data validation. Excellent communication and stakeholder management skills.
03/10/2025
Full time
Senior Guidewire ClaimCenter Developer 6+ years' experience with ClaimCenter, Guidewire Certified. Strong in Gosu, Java, SOAP/REST, Studio, Messaging, Data Model, Rules & Workflows. Lead development, integrations, mentoring, code reviews, and performance optimization. Agile/Scrum experience with solid problem-solving and communication skills. Guidewire ClaimCenter Business Specialist/Analyst 5+ years' experience with ClaimCenter, Guidewire Certified (preferred). Skilled in requirements gathering, functional specs, user stories, workshops, and solution validation. Strong in configuration, integrations, data mapping, UAT, and end-user training. Knowledge of insurance regulations, Agile (Jira), and SQL for data validation. Excellent communication and stakeholder management skills.
