Brief Summary
This role offers a unique opportunity to lead MLOps initiatives, transforming the technical foundation for applications and cloud infrastructure. You will drive innovation and best practices in AI-driven MLOps for production-scale deployment.
Responsibilities
- Define and execute the roadmap for MLOps infrastructure transformation encompassing edge and cloud. Manage AI projects, including planning, execution, monitoring, and reporting on project milestones and risks. Champion Agile and Scrum methodologies to optimize project outcomes. Lead migrations while ensuring performance, security, and cost-efficiency. Establish data preparation strategies to enhance data usability for MLOps. Direct a team of data scientists to develop future AI and MLOps strategies. Collaborate with cross-functional teams to ensure alignment with project objectives. Prepare comprehensive reports on project progress and challenges while presenting findings to stakeholders. Contribute to the development and maintenance of technical documentation and standards. Mentor junior engineers and facilitate their professional growth.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related field in machine learning. Minimum of 6 years of experience in MLOps, AI, Cloud, or DevOps, particularly in manufacturing environments. At least 4 years of experience in building and deploying large-scale machine learning applications. A minimum of 2 years of direct management experience leading agile teams. Proficiency in AI/ML project coordination, data handling, and model training/testing. Deep expertise with CI/CD pipelines, MLOps practices, and cloud infrastructure. Familiarity with databases such as PostgreSQL and InfluxDB, including cloud migration experience. Hands-on experience with Kubernetes, OpenShift, and cloud-native architectures. Strong leadership, communication, and stakeholder management abilities. Relevant certifications, including Certified Kubernetes Administrator (CKA) and AWS certifications. Demonstrated experience in performance monitoring and optimization in cloud settings.
