MLOps Engineer
Role Overview
This senior MLOps Engineer role involves designing and managing containerized GPU deployments with Docker, optimizing Kubernetes clusters for scalable ML deployments, and integrating deep learning frameworks like TensorFlow and Keras into production pipelines. The engineer will work on multi-modal projects processing audio, video, and image data, monitor model performance and drift, and collaborate with data science teams to support end-to-end machine learning pipelines from data ingestion to deployment.
Perks & Benefits
This is a fully remote position offering flexibility in work location. The role involves cross-functional collaboration with data science and other teams, suggesting a collaborative culture focused on innovation. Working at Zzazz provides opportunities to work on cutting-edge AI and economic technology with global impact, though specific benefits like healthcare or professional development aren't detailed.
Full Job Description
Roles and Responsibilities
• Infrastructure Development: Design, implement, and manage containerized GPU deployments using Docker.
• Multi-modal Projects: Integrate and deploy machine learning models for audio, video, and image processing tasks.
• Framework Integration: Collaborate with data science teams to ensure seamless integration of TensorFlow, Keras, and other deep learning frameworks into production pipelines.
• Kubernetes Management: Optimize and manage Kubernetes clusters for scalable and efficient deployment.
• Model Optimization: Utilize ONNX and C-based deployments for optimized model execution and scalability.
• Model Monitoring: Monitor model performance, detect model drift, and ensure the robustness of deployed models in production environments.
• Pipeline Support: Provide support for end-to-end machine learning pipelines, from data ingestion to model deployment.
• Cross-functional Collaboration: Ensure effective communication with cross- functional teams to align on project goals and deliverables.
Skillset
• Proficiency in Python programming.
• Hands-on experience with containerized GPU deployments using Docker.
• Proven track record of working on multi-modal projects involving audio, video, and image processing.
• Strong expertise in deep learning frameworks such as TensorFlow and Keras.
• Experience with Kubernetes for managing scalable machine learning deployments.
• Familiarity with ONNX and C-based model deployment frameworks.
• Knowledge of model monitoring techniques, including model drift detection and management.
Experience
• 4+ years of experience in a similar role
Qualification
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
About Zzazz
Zzazz is pioneering the next global information economy by transforming how digital content is valued and experienced. Our advanced Economic AI quantifies the real-time value and price of content, turning it into dynamic assets that reshape industries worldwide. At Zzazz, you'll join a team of innovators pushing the boundaries of AI and economics to create meaningful impact on a global sca
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