Strong expertise in Python for building, training, and deploying machine learning models.
Deep understanding of transformer architectures, large language models (LLMs), and generative AI techniques.
Experience with frameworks such as PyTorch / TensorFlow.
Knowledge of fine-tuning, prompt engineering, embeddings, and vector databases.
Hands-on experience with cloud platforms (AWS / GCP / Azure) for large-scale ML deployment.
Proficiency in MLOps tools and practices for model lifecycle management.
Familiarity with scalability, optimization, and distributed training methods.
Awareness of AI ethics, security, and compliance :
Architect and design end-to-end solutions leveraging LLMs and GenAI capabilities.
Develop, fine-tune, and optimize large-scale NLP models.
Collaborate with product and engineering teams to integrate models into production systems.
Define best practices for scalable, secure, and efficient model deployment.
Stay updated on emerging GenAI research and frameworks and bring innovation to projects.
(ref : hirist.tech)
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