Senior Principal Data Engineer

You should have hands-on experience in big data processing, mining, and visualization. Design and develop deep learning systems using frameworks like TensorFlow and PyTorch. Efficiently plan and continuously improve existing systems. Provide team mentorship and excel in innovating, scaling, adapting, addressing data drift, and improving system performance. Research and apply advanced AI/ML techniques, including Generative AI models (e.g., GPT, LLaMA) and NLP architectures. Experience in on-premises/Hadoop ecosystem is essential. For Principal Data Engineering roles, a minimum of 13+ years of experience is required, while for Data Engineering roles, 5+ years of experience is necessary. Proven expertise in AI/ML, NLP, and proficiency in Python, Java, Pyspark, Apache Spark, Hadoop, Cassandra, TensorFlow, PyTorch, Scikit-learn, Django, Flask, Numpy, and Pandas are expected. Knowledge of data structures, SQL, MongoDB, multi-threading, RESTful APIs, and Power BI for data visualization is crucial. Familiarity with networking, post-production support, and lifecycle management of ML systems is beneficial. Exceptional problem-solving skills, strong leadership capabilities, and excellent communication skills are required. A strong understanding of statistics, probability, algorithms, and optimization techniques is essential. Experience deploying ML applications on GCP, Azure, or AWS is preferred.,