Job Description
Responsibilities:
· Design and develop production-grade AI and machine learning models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting).
· Lead model lifecycle management from experimentation and prototyping to deployment and monitoring.
· Collaborate with cross-functional teams (product, data engineering, MLOps, and business) to define AI-driven features and services.
· Perform feature engineering, data wrangling, and exploratory data analysis on large-scale structured and unstructured datasets.
· Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices.
· Mentor junior AI engineers, guiding them in model development, evaluation, and deployment.
· Continuously improve model performance by leveraging new research, retraining on new data, and optimizing pipelines.
· Stay current with the latest developments in AI, machine learning, and deep learning through research,...
· Design and develop production-grade AI and machine learning models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting).
· Lead model lifecycle management from experimentation and prototyping to deployment and monitoring.
· Collaborate with cross-functional teams (product, data engineering, MLOps, and business) to define AI-driven features and services.
· Perform feature engineering, data wrangling, and exploratory data analysis on large-scale structured and unstructured datasets.
· Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices.
· Mentor junior AI engineers, guiding them in model development, evaluation, and deployment.
· Continuously improve model performance by leveraging new research, retraining on new data, and optimizing pipelines.
· Stay current with the latest developments in AI, machine learning, and deep learning through research,...
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