Data/Machine Learning Infrastructure Engineer

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Requirements:

• 3+ years in AI/ML deployment, solution engineering, or similar roles.
• Proficiency with Apache Kafka for managing and scaling event-stream pipelines.
• Familiarity with LangChain, TensorFlow, PyTorch, and cloud platforms like AWS, Azure, and Google Cloud.
• Experience with RESTful APIs, microservices, and container technologies like Docker and Kubernetes.
• Strong data engineering practices and experience in handling unstructured data.

Responsibilities:

• Deploy AI and machine learning models to drive insights from telecom event streams.
• Develop and maintain Kafka pipelines for real-time data processing.
• Manage and optimize model training, tuning, and retraining workflows.
• Collaborate with data engineers and product teams on data needs and model integration.
• Implement monitoring solutions for model performance and resolve issues proactively.
• Document processes, configurations, and best practices for knowledge sharing.