Oracle
Data Scientist 3 – AI Engineer (LLM/RAG)
Job Description
Responsibilities • You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to ensure the seamless integration of machine learning capabilities into our solutions • Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems • Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts • Fine-tune and optimize large language models such as Cohere for specific use cases in the technology, Construction & utilities domain. • Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products • Collaborate with software engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance • Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage • Provide technical leadership and mentorship to junior members of the machine learning team, fostering a culture of continuous learning and growth Job description • We are Technology company building new products to solve industries problems specifically in Construction & utilities. Our mission is to enhance customer experience, streamline operations, and drive growth. • We’re seeking a highly skilled Senior Machine Learning Engineer to join our passionate team and contribute to the development of cutting-edge RAG models and large language models, leveraging advanced techniques in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG). • As a Senior Machine Learning Engineer specializing in Conversational AI, you will play a pivotal role in architecting, developing, and deploying state-of-the-art models to power our conversational AI product suite. • You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to ensure the seamless integration of machine learning capabilities into our solutions.
Key Responsibilities: • Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems. • Utilize & build vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts. • Fine-tuned and optimized use of large language models such as Cohere for specific use cases in the technology & Industries (Construction, Utilities) domain. • Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products. • Collaborate with software engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance. • Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage. • Provide technical leadership and mentorship to junior members of the machine learning team, fostering a culture of continuous learning and growth.
Qualifications: • Master’s degree or higher in Computer Science, Engineering, Mathematics, or related field. Advanced degree preferred. • 5+ years of experience in machine learning engineering, with a focus on building and deploying conversational AI solutions. • Proven expertise in developing RAG models, working with vector databases, and fine-tuning large language models. • Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or JAX. • Experience with cloud platforms (e.g., AWS, OCI) and containerization technologies (e.g., Docker, Kubernetes). • Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation. • Excellent problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems. • Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders • Experience with OCI/AWS and related services is desirable.
Career Level – IC3
Responsibilities
• You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to ensure the seamless integration of machine learning capabilities into our solutions
• Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems
• Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts
• Fine-tune and optimize large language models such as Cohere for specific use cases in the technology, Construction & utilities domain.
• Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products
• Collaborate with software engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance
• Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage
• Provide technical leadership and mentorship to junior members of the machine learning team, fostering a culture of continuous learning and growth
Job description
• We are Technology company building new products to solve industries problems specifically in Construction & utilities. Our mission is to enhance customer experience, streamline operations, and drive growth.
• We’re seeking a highly skilled Senior Machine Learning Engineer to join our passionate team and contribute to the development of cutting-edge RAG models and large language models, leveraging advanced techniques in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG).
• As a Senior Machine Learning Engineer specializing in Conversational AI, you will play a pivotal role in architecting, developing, and deploying state-of-the-art models to power our conversational AI product suite.
• You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to ensure the seamless integration of machine learning capabilities into our solutions.
Key Responsibilities:
• Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems.
• Utilize & build vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
• Fine-tuned and optimized use of large language models such as Cohere for specific use cases in the technology & Industries (Construction, Utilities) domain.
• Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products.
• Collaborate with software engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance.
• Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage.
• Provide technical leadership and mentorship to junior members of the machine learning team, fostering a culture of continuous learning and growth.
Qualifications:
• Master’s degree or higher in Computer Science, Engineering, Mathematics, or related field. Advanced degree preferred.
• 5+ years of experience in machine learning engineering, with a focus on building and deploying conversational AI solutions.
• Proven expertise in developing RAG models, working with vector databases, and fine-tuning large language models.
• Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or JAX.
• Experience with cloud platforms (e.g., AWS, OCI) and containerization technologies (e.g., Docker, Kubernetes).
• Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.
• Excellent problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.
• Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders
• Experience with OCI/AWS and related services is desirable.
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Disclaimer:
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