Machine Learning Engineer
1 week ago
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 scale.
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.
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