Description review
MLOps Engineer
Arrise · Portugal · back to the listing
HR standards
54/100
needs work
Title ↔ description
74/100
solid
Reads as
Unclear
no confident match
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
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What the listing never says
- 17 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
What you will do
• 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 application testing, validation, and deployment
• Monitor and maintain deployed APIs to ensure performance, reliability, and security.
• Create and manage internal platforms to configure and manage ML systems in production.
• Develop observability dashboards and alerting systems for model and infrastructure health.
• Implement unit and integration tests for ML code, pipelines, and deployment workflows.
• Follow security best practices in containerized deployments and data handling.
What you bring
• 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 architecting scalable and reliable ML systems.
• Strong knowledge of version control systems, package management, dependency tracking.
• Expertise in containerization using Docker for scalable and maintainable system deployments.
• Experience with monitoring, logging, and alerting for ML systems and infrastructure.
• Knowledge of general Machine Learning concepts and algorithms.
• Proven experience deploying and managing ML models in production environments.
• Knowledge of data modelling, ETL processes, and database systems (SQL and NoSQL)
About us
ARRISE is a global leader in software development and services for the iGaming industry, bringing together more than 2,500 professionals operating across more than 12 locations worldwide.
From concept through to delivery, we combine technical expertise, creativity and industry knowledge to develop products, platforms and services that shape player experiences and support some of the industry's leading brands.
We are best known for the work we deliver for Pragmatic Play, creating and supporting technology, products and specialists services enjoyed by millions of players worldwide.
Originally posted on Himalayas
• 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 application testing, validation, and deployment
• Monitor and maintain deployed APIs to ensure performance, reliability, and security.
• Create and manage internal platforms to configure and manage ML systems in production.
• Develop observability dashboards and alerting systems for model and infrastructure health.
• Implement unit and integration tests for ML code, pipelines, and deployment workflows.
• Follow security best practices in containerized deployments and data handling.
What you bring
• 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 architecting scalable and reliable ML systems.
• Strong knowledge of version control systems, package management, dependency tracking.
• Expertise in containerization using Docker for scalable and maintainable system deployments.
• Experience with monitoring, logging, and alerting for ML systems and infrastructure.
• Knowledge of general Machine Learning concepts and algorithms.
• Proven experience deploying and managing ML models in production environments.
• Knowledge of data modelling, ETL processes, and database systems (SQL and NoSQL)
About us
ARRISE is a global leader in software development and services for the iGaming industry, bringing together more than 2,500 professionals operating across more than 12 locations worldwide.
From concept through to delivery, we combine technical expertise, creativity and industry knowledge to develop products, platforms and services that shape player experiences and support some of the industry's leading brands.
We are best known for the work we deliver for Pragmatic Play, creating and supporting technology, products and specialists services enjoyed by millions of players worldwide.
Originally posted on Himalayas