
AI Model Development Specialist
4 days ago
The role of Machine Learning Operations Engineer involves collaborating closely with cross-functional teams to design, develop, and deploy machine learning models that meet business requirements.
- Main Responsibilities:
Prepare, clean, and process large datasets; build and maintain data pipelines.
Develop and implement machine learning models for various applications (classification, regression, clustering, recommendations, etc.).
Engineer features and optimize model performance through hyperparameter tuning and validation.
Automate model building, training, and deployment by creating continuous integration and continuous delivery pipelines.
Stay updated on new tools and techniques in machine learning and AI.
Qualifications:
Bachelor's or Master's in Computer Science, Engineering, Mathematics, Statistics, or a related field.
3-5 years of hands-on experience in AI/ML engineering and Python, with a demonstrable focus on building production-ready models.
Strong understanding of machine learning algorithms, deep learning architectures, natural language processing (NLP), and information retrieval techniques (e.g., RAG).
Proven ability to deploy and manage AI/ML solutions on at least one major cloud platform.
Experience with MLOps principles and tools for model deployment, monitoring, and lifecycle management.
Experience with MLOps frameworks like Kubeflow, MLFlow, DataRobot, Airflow, containerization using Docker, and Kubernetes, OpenShift.
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