Research Engineer (MLOps, AI Systems For Manufacturing Projects) (ID: 675133) - #1095960

We are looking for a skilled and motivated Software Engineer with a strong background in Machine Learning Operations (MLOps) to join our client's team. In this role, you will play a critical part in deploying machine learning models and implementing best practices for scalable and reliable AI systems. You will work closely with cross-functional research and engineering teams to streamline model deployment, optimize AI pipelines, and contribute to the delivery of high-quality, production-ready ML/AI solutions.

Key Responsibilities:

• Design, develop, test, and maintain enterprise-grade software systems with a focus on machine learning and AI integration.

• Implement MLOps best practices to automate and streamline model training, deployment, monitoring, and maintenance.

• Collaborate with data scientists and software engineers to integrate machine learning models into production systems.

• Optimize AI/ML pipelines for performance, scalability, and reliability in cloud-native or on-premises environments.

• Develop and optimize deep learning architectures and machine learning algorithms for improved accuracy and efficiency.

• Conduct performance tuning and model evaluation to ensure optimal system behavior.

• Leverage containerization and orchestration technologies for scalable deployment of microservices and AI models.

• Stay abreast of emerging technologies and advancements in AI/ML, MLOps, and software engineering.

• Engage with cross-functional stakeholders to gather requirements and ensure effective solution delivery.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• Minimum of 8 years’ experience as a Software Developer/Engineer, with a strong focus on backend and ML-related systems.

• Proficient in C# .NET, Python, and Angular for full-stack or backend development.

• Solid experience in cloud-native technologies, including microservices, DevSecOps, and containerization (e.g., Docker, Kubernetes).

• Practical knowledge of CI/CD pipelines using tools such as Git, Jenkins, Artifactory, SonarQube, and Docker registries.

• Hands-on experience deploying and managing containerized microservices on on-premises or public cloud platforms.

• Familiarity with deep learning architectures, natural language processing (NLP), and modern AI frameworks.

• Strong analytical and troubleshooting skills, with a keen attention to detail.

Interested candidate who wish to apply for the advertised position, please click on “Apply Now”. 

We regret that only shortlisted candidates will be notified.

EA License NO.: 01C4394

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