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1 day ago
This role entails the design and implementation of scalable data intelligence systems, integrating diverse data sources. The ideal candidate will have expertise in Generative AI models, encompassing LLMs, GANs, and Diffusion Models.
Key Responsibilities:- Design and implement data pipelines, feature stores, and model monitoring systems to enhance efficiency and reliability.
- Develop and fine-tune Generative AI models for tasks such as text generation, synthetic data creation, and content automation to meet business requirements.
- Collaborate with cross-functional teams to deploy AI solutions into production environments, ensuring seamless integration and deployment.
- Apply prompt engineering techniques to optimize LLM performance for various business use cases, leveraging domain expertise to drive results.
- Conduct experiments and A/B testing to evaluate model performance and business impact, informing strategic decisions.
The successful candidate will possess a strong understanding of data governance, privacy, and ethical AI standards, applying this knowledge to drive innovation and excellence.
Requirements:- Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field.
- 3-5 years of experience in data science, machine learning, or AI engineering, with a focus on delivering high-quality solutions.
- Hands-on experience with LLMs (e.g., GPT, Claude, LLaMA) and frameworks like Hugging Face, LangChain, or OpenAI APIs, driving innovation and progress.
- Proficiency in Python, SQL, and cloud platforms (AWS, Azure, or GCP), ensuring seamless integration and deployment.
Prior experience with knowledge graphs, semantic search, or data fabric architectures is beneficial but not mandatory.
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