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Mid-level AI role in a metro market with broad generative-AI demand increases applicant competition.
Generative ML skills transfer across industries but require deep domain expertise, raising specificity.
Requires specialized generative AI and MLOps expertise but no explicit years requirement specified.
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Design, develop, and deploy state-of-the-art generative AI models (LLMs, Diffusion Models, GANs, VAEs) for various applications.
Optimize and integrate generative AI solutions into product pipelines with API development and robust MLOps practices.
Conduct research, testing, and validation to ensure model performance, scalability, reliability, and ethical compliance.
Work Experience Required: Not explicitly mentioned in the JD
Strong expertise in designing and implementing generative AI models and familiarity with Large Language Models, GANs, VAEs, Diffusion Models.
Experience with MLOps for deploying and maintaining AI models in production environments.
Not explicitly mentioned: educational qualifications, specific notice period, or location requirements.
Technically proficient in developing and fine-tuning state-of-the-art generative AI systems with a practical focus on deployment and scalability.
Experienced in collaborative, cross-functional environments involving data scientists, ML engineers, and product managers to translate AI research into production-level features.
Focused on innovation through research and applying latest advancements in generative AI for novel product solutions.