Staff Data Engineer

Required Skills & Experience
• Strong foundation in time series forecasting, deep learning, and optimization theory, with a focus on sequence modeling and attention-based architectures. \n• Experience in training and deploying transformer-based neural networks (e.g., TFT, LSTM, GPT variants) for real-world business applications. \n• Proficient in Python, SQL, and hands-on with PyTorch, TensorFlow/Keras, Scikit-learn, and statsmodels. \nDemonstrated ability to work on GPU-based model training pipelines, and exposure to managing experimentation at scale.

Nice to Have Skills & Experience
• Enterprise level experience preferred\n\t• Deep Learning\n\t• Agentic\n\t• Gen AI\n\t• Language Models

Job Description
• Develop scalable time series forecasting systems leveraging global models like Temporal Fusion Transformers, N-BEATS, and PATCHTST, enabling robust forecasting across thousands of retail and e-commerce time series. \n• Foundational Knowledge on advanced regression. \n• Apply generative AI to synthesize time series data, enhance model training pipelines, and build intelligent NLP-based assistants for analytics enablement. \n• Design and train large-scale neural networks for time series, anomaly detection, and causal inference, with deployment via automated batch pipelines \n• Build and maintain production-ready applications on cloud platforms, integrated with internal systems to deliver insights at scale. \nCollaborate with cross-functional teams to define objectives, formulate hypotheses, and deploy models that directly influence decision-making.