MLOps Engineer

Company Description Solutyics is a technology-focused company dedicated to creating a world where Data and AI unlock new possibilities for businesses. The team specializes in AI, Machine Learning, Data Engineering, and Advanced Data Analytics to help clients solve complex challenges and achieve long-term success. Solutyics emphasizes understanding each client’s unique needs and delivering tailored solutions that align with their goals. The company values transparent relationships built on integrity and a shared commitment to successful outcomes.Role Description The MLOps Engineer role is a full-time, on-site position based in Dubai, United Arab Emirates. In this role, the MLOps Engineer will design, build, and maintain scalable machine learning deployment pipelines and production environments. Daily responsibilities include automating model training and deployment, managing CI/CD workflows, monitoring model performance, and ensuring reliability and security of ML services. The role also involves collaborating with data scientists, ML engineers, and data engineers to operationalize models, optimize infrastructure costs, and improve system performance. The MLOps Engineer will contribute to best practices for observability, version control, and governance of ML assets, while supporting continuous improvement across AI and data projects.Qualifications Strong foundation in Machine Learning operations, including model deployment, monitoring, and lifecycle management.Experience with cloud platforms and infrastructure-as-code tools for building and maintaining ML environments.Proficiency in DevOps practices such as CI/CD, containerization, and orchestration for ML workflows.Ability to collaborate with cross-functional teams in AI, Data Engineering, and Advanced Analytics.Mechanical Engineering, Machine Design, and Computer-Aided Design (CAD) skills as beneficial for projects involving physical systems or hardware integration.Experience in Project Management and Research and Development (R&D) to drive structured experimentation and delivery.Strong programming skills (e.g., Python) and familiarity with ML frameworks and data pipelines.Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.Clear communication skills and the ability to document processes and standards effectively.