Job Description: EY GDS – Data and Analytics (D&A) – Sr.Manager – Quantum
We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 14+ years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
Your technical responsibilities:
- Contribute to the design and implementation of state-of-the-art AI solutions.
- Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
- Collaborate with stakeholders to identify business opportunities and define AI project goals.
- Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
- Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
- Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
- Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
- Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
- Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
- Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
- Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
- Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
- Ensure compliance with data privacy, security, and ethical considerations in AI applications.
- Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
- Minimum 14+ years of experience in Data Science and Machine Learning.
- Working knowledge of Quantum Engineering
- Quantum Machine Learning (Data encoding, HHL Algorithm implementation, Quantum linear regression, Euclidean Distance calculations, K-Means clustering, PCA, SVM implementation using Qiskit)
- Quantum Algorithms (Qiskit, Deutsch Jozsa, Bernstein Vajirani, Simon’s Algorithms)
- Quantum Deep Learning (Hybrid Quantum Neural Networks)
- Open-source Quantum Frameworks
- Qiskit based programming
- Quantum Optimization (Variational Quantum Eigensolver, Expectation Computation, VQE algorithm, Max-cut graph clustering, Adiabatic Theorem, Approximate Optimization Algorithm, etc)
- Python as a Programming Language
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