
AI Infrastructure Specialist
2 days ago
The ideal candidate will possess expertise in designing and implementing machine learning infrastructure to support various applications.
- Develop, implement and maintain data pipelines to optimize model performance.
- Design and deploy scalable, reliable, and secure AI infrastructure on cloud platforms.
- Implement automated CI/CD/CT pipelines for efficient model building, training, and deployment.
- Collaborate with cross-functional teams to ensure alignment between technical capabilities and business objectives.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or related field.
- At least 3-5 years of hands-on experience in AI/ML engineering and Python, with a strong focus on production-ready models.
- Excellent understanding of machine learning algorithms, deep learning architectures, natural language processing (NLP), and information retrieval techniques.
- Proven ability to design and deploy AI/ML solutions on major cloud platforms.
- Experience with MLOps principles and tools for model deployment, monitoring, and lifecycle management.
- Knowledge of MLOps frameworks like Kubeflow, MLFlow, DataRobot, Airflow, containerization using Docker, and Kubernetes orchestration.
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