MLOps Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Design, deploy, and operate production-grade machine learning systems for a global iGaming platform. Own the full MLOps lifecycle: scalable inference and serving, automated data/training/inference pipelines, CI/CD for testing and deployment, and reliable API operations. Build internal ML platforms, implement monitoring/alerting and observability for model and infrastructure health, and ensure secure containerized deployments with strong testing practices.

Location: Malta

Workplace: Remote

Employment Type: Full time · Permanent

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design and operate scalable inference and serving systems for ML workloads.
•Design and maintain automated data, training, and inference pipelines.
•Build and manage CI/CD pipelines for testing, validation, and deployment.
•Monitor and maintain deployed APIs for performance, reliability, and security.
•Develop observability dashboards and alerting for model and infrastructure health, and implement unit/integration tests.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
•Proficient in Python with strong software architecture and development skills.
•Expertise in cloud platforms, preferably Azure, for scalable and reliable ML systems.
•Expertise in containerization using Docker for scalable, maintainable deployments.
•Proven experience deploying and managing ML models in production; knowledge of data modeling, ETL, and databases (SQL and NoSQL).

Education:High School in Computer Science, Engineering, or a related field

Tech Stack:PythonAzureDockerSQLNoSQL

Company Brief

Arrise

Arrise provides a cloud platform that helps property owners, facilities teams and compliance managers centralize building safety, maintenance and regulatory documentation, automate inspections and workflows, and streamline reporting to reduce risk and ensure operational compliance.

Industry: Facility Management

Website

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Arrise

4 days ago

MLOps Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: Malta

Workplace: Remote

Employment Type: Full time · Permanent

Job Function: DevOps, Cloud & Infrastructure

Key Responsibilities

•Design and operate scalable inference and serving systems for ML workloads.
•Design and maintain automated data, training, and inference pipelines.
•Build and manage CI/CD pipelines for testing, validation, and deployment.
•Monitor and maintain deployed APIs for performance, reliability, and security.
•Develop observability dashboards and alerting for model and infrastructure health, and implement unit/integration tests.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
•Proficient in Python with strong software architecture and development skills.
•Expertise in cloud platforms, preferably Azure, for scalable and reliable ML systems.
•Expertise in containerization using Docker for scalable, maintainable deployments.
•Proven experience deploying and managing ML models in production; knowledge of data modeling, ETL, and databases (SQL and NoSQL).

Education:High School in Computer Science, Engineering, or a related field

Tech Stack:PythonAzureDockerSQLNoSQL

Company Brief

Arrise

Industry: Facility Management

Website