Project Manager, MLOps

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.

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