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Senior Research Engineer, Smart Virtual Systems
Salary undisclosed
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Key Roles and Responsibilities:
• Develop, test, and maintain enterprise system and applications, with a focus in ML/AI systems.
• Implement MLOps best practices to automate model training, deployment, and monitoring processes.
• Implement and optimize machine learning algorithms and deep learning architectures.
• Collaborate with data scientists and software engineers to integrate machine learning solutions into existing systems and deliver high-quality software products.
• Optimize AI pipelines for scalability, reliability, and performance.
• Conduct performance analysis and optimization to improve model efficiency and accuracy.
• Stay updated on the latest advancements in software engineering, AI/ML technologies and best practices.
Job Requirements:
• Bachelor or Master Degree in Computer Science/Engineering or relevant disciplines.
• Must have a minimum of 5 years of experience as a Software Developer/Engineer.
• Hands-on experience in Cloud Native Technologies such as in micro-services, DevSecOps, and Containerisation Technologies.
• Proficiency in designing and developing microservices and software systems using C# .NET, Python and angular.
• A good understanding of CI/CD Pipelines in a distributed environment using Git, Artifactory, Jenkins, SonarQube, Docker registry, etc.
• Hands-on experience with deploying and managing microservices using container orchestration platforms (on-prem/public cloud).
• Can do attitude and happy to interface with multiple stakeholders.
• Excellent troubleshooting, follow-through, and problem solving skills, with attention to detail.
• Excellent verbal and written communication skills.
• Hands-on experience with machine learning frameworks/libraries.
• Understanding of machine learning algorithms and techniques.
• Familiarity with deep learning architectures and natural language processing (NLP) techniques.
• Develop, test, and maintain enterprise system and applications, with a focus in ML/AI systems.
• Implement MLOps best practices to automate model training, deployment, and monitoring processes.
• Implement and optimize machine learning algorithms and deep learning architectures.
• Collaborate with data scientists and software engineers to integrate machine learning solutions into existing systems and deliver high-quality software products.
• Optimize AI pipelines for scalability, reliability, and performance.
• Conduct performance analysis and optimization to improve model efficiency and accuracy.
• Stay updated on the latest advancements in software engineering, AI/ML technologies and best practices.
Job Requirements:
• Bachelor or Master Degree in Computer Science/Engineering or relevant disciplines.
• Must have a minimum of 5 years of experience as a Software Developer/Engineer.
• Hands-on experience in Cloud Native Technologies such as in micro-services, DevSecOps, and Containerisation Technologies.
• Proficiency in designing and developing microservices and software systems using C# .NET, Python and angular.
• A good understanding of CI/CD Pipelines in a distributed environment using Git, Artifactory, Jenkins, SonarQube, Docker registry, etc.
• Hands-on experience with deploying and managing microservices using container orchestration platforms (on-prem/public cloud).
• Can do attitude and happy to interface with multiple stakeholders.
• Excellent troubleshooting, follow-through, and problem solving skills, with attention to detail.
• Excellent verbal and written communication skills.
• Hands-on experience with machine learning frameworks/libraries.
• Understanding of machine learning algorithms and techniques.
• Familiarity with deep learning architectures and natural language processing (NLP) techniques.