Role Description The MLOps Engineer will be a full time, on-site team member based in Abroad, responsible for building, deploying, and maintaining machine learning pipelines and infrastructure that support data-driven decision-making within the organization. Day-to-day tasks include collaborating with data scientists and developers to operationalize models, automating workflows from model training to production deployment, and monitoring performance to ensure reliability, scalability, and security. The role involves optimizing compute resources, managing version control for models and data, and implementing CI/CD practices for ML services.

The MLOps Engineer will also document systems and processes, participate in cross-functional meetings to translate business needs into technical solutions, and troubleshoot production issues to minimize downtime and improve system stability.

Qualifications

Engineering and design skills, including Mechanical Engineering and Machine Design, with the ability to apply engineering principles to technical systems and workflows.

Proficiency in Computer-Aided Design (CAD) for modeling, visualization, and documentation of components, systems,



or infrastructure relevant to technology solutions.

Project Management skills to plan, coordinate, and deliver engineering or technology projects on time and within scope, including stakeholder communication and risk management.

Experience in Research and Development (R&D;), with the ability to investigate new methods, tools, and technologies, and translate findings into practical improvements.

Strong foundation in software engineering or related technical discipline (e.g., computer science, data engineering), with experience in scripting or programming for automation.

Understanding of machine learning lifecycles, deployment practices, and modern cloud or on-premise infrastructure tools commonly used in MLOps.

Effective communication and teamwork skills, with the ability to work closely with multidisciplinary teams and adapt to evolving business requirements.

Bachelor’s degree in engineering, computer science, or a related technical field; relevant certifications in ML, DevOps, or cloud platforms are an advantage.

📌 MLOps Engineer (Indore)
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📍 Indore