Applied AI/ML Engineer
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The role
Design, develop, and deploy AI-powered features into production systems.
Apply supervised, unsupervised, and deep learning techniques to structured and unstructured data.
Build and evaluate models for classification, ranking, prediction, NLP, or anomaly detection.
Develop GenAI solutions (LLM-based workflows, retrieval-augmented generation, and agents) and integrate them into workflows.
Translate business needs into ML problem statements, metrics, and experiments; implement data pipelines and feature engineering to support training and inference.
Collaborate with software engineers to integrate models into APIs, services, and user-facing applications; monitor bias, drift, and reliability while balancing accuracy, latency, and cost.
Apply supervised, unsupervised, and deep learning techniques to structured and unstructured data.
Build and evaluate models for classification, ranking, prediction, NLP, or anomaly detection.
Develop GenAI solutions (LLM-based workflows, retrieval-augmented generation, and agents) and integrate them into workflows.
Translate business needs into ML problem statements, metrics, and experiments; implement data pipelines and feature engineering to support training and inference.
Collaborate with software engineers to integrate models into APIs, services, and user-facing applications; monitor bias, drift, and reliability while balancing accuracy, latency, and cost.
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