AIML Lead

Role Overview: As an AI Software Lead with 7-10 years of relevant experience, your main responsibility will be to design, develop, and deploy scalable AI solutions with a focus on production. You will need to emphasize MLOps best practices and have deep proficiency in AI model engineering. Key Responsibilities: - Training and fine-tuning large language models (LLMs) and other deep learning architectures. - Model optimization, quantization, and deployment to ensure low latency and high throughput. - Conducting model evaluation and monitoring in production environments. - Building and integrating AI capabilities such as computer vision, NLP, and recommendation systems into production-grade Web/Mobile App software. - Scaling AI systems for high-volume, real-time applications using Cloud-Native or Edge-AI technologies. - Understanding data pipelines and feature engineering for AI applications. Qualifications Required: - 7-10 years of relevant experience in AI software development. - Proficiency in AI model engineering and MLOps best practices. - Experience in training and fine-tuning large language models and deep learning architectures. - Strong knowledge of model optimization, quantization, and deployment for performance. - Ability to build and integrate AI capabilities into Web/Mobile App software. - Familiarity with scaling AI systems for high-volume, real-time applications. - Understanding of data pipelines and feature engineering for AI applications. Role Overview: As an AI Software Lead with 7-10 years of relevant experience, your main responsibility will be to design, develop, and deploy scalable AI solutions with a focus on production. You will need to emphasize MLOps best practices and have deep proficiency in AI model engineering. Key Responsibilities: - Training and fine-tuning large language models (LLMs) and other deep learning architectures. - Model optimization, quantization, and deployment to ensure low latency and high throughput. - Conducting model evaluation and monitoring in production environments. - Building and integrating AI capabilities such as computer vision, NLP, and recommendation systems into production-grade Web/Mobile App software. - Scaling AI systems for high-volume, real-time applications using Cloud-Native or Edge-AI technologies. - Understanding data pipelines and feature engineering for AI applications. Qualifications Required: - 7-10 years of relevant experience in AI software development. - Proficiency in AI model engineering and MLOps best practices. - Experience in training and fine-tuning large language models and deep learning architectures. - Strong knowledge of model optimization, quantization, and deployment for performance. - Ability to build and integrate AI capabilities into Web/Mobile App software. - Familiarity with scaling AI systems for high-volume, real-time applications. - Understanding of data pipelines and feature engineering for AI applications.