Job Description
Key Responsibilities
- Design, develop, and deploy machine learning, statistical, deep learning, and Generative AI models for enterprise use cases.
- Perform data exploration, feature engineering, model training, evaluation, and optimization on structured and unstructured datasets.
- Build predictive, prescriptive, and descriptive analytics solutions aligned with business objectives.
- Develop and fine-tune AI/ML models including classical ML, Deep Learning, NLP, Time-Series Forecasting, and Large Language Models (LLMs).
- Design and implement Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources and Vector Databases.
- Build reusable Prompt Templates and Prompt Engineering strategies for enterprise AI applications.
- Apply Anthropic Constitutional AI principles to develop protected, reliable, and responsible AI applications.
- Collaborate with Data Engineering and Platform teams to productionize models using MLOps and LLMOps best practices.
- Develop AI experimentation, evaluation, and benchmarking frameworks using MLflow and enterprise AI evaluation methodologies.
Design, develop, and deploy machine learning, statistical, deep learning, and Generative AI models for enterprise use cases.
Perform data exploration, feature engineering, model training, evaluation, and optimization on structured and unstructured datasets.Build predictive, prescriptive, and descriptive analytics solutions aligned with business objectives.Develop and fine-tune AI/ML models including classical ML, Deep Learning, NLP, Time-Series Forecasting, and Large Language Models (LLMs).Design and implement Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources and Vector Databases.Build reusable Prompt Templates and Prompt Engineering strategies for enterprise AI applications.Apply Anthropic Constitutional AI principles to develop protected, reliable, and responsible AI applications.Collaborate with Data Engineering and Platform teams to productionize models using MLOps and LLMOps best practices.Develop AI experimentation, evaluation, and benchmarking frameworks using MLflow and enterprise AI evaluation methodologies.Engineer - Generative AI
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