AI/ML Specialist for Sports Companion GPT

4 days ago

vellore, India beBeeArtificialIntelligence Full time

Job Title: AI/ML Specialist for Sports Companion GPTJob OverviewWe are seeking a skilled AI/ML specialist to develop Sports Companion GPT, a cutting-edge platform for sports applications. The ideal candidate will have expertise in designing and developing AI models for Sports Companion GPT, leveraging conventional machine learning techniques and generative AI.Key Responsibilities:Develop AI models for Sports Companion GPT, incorporating conventional ML techniques with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics.Fine-tune pre-trained generative AI models using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports.Design and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications.Process and analyze large, complex datasets to prepare data for training both ML and generative AI models.Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases.Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications.Collaborate with sports analysts, data engineers, and domain experts to incorporate domain knowledge into Sports Companion GPT and align with business objectives.Deploy models into production environments, ensuring efficient inference for real-time or near-real-time sports applications.Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks.Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing.Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs.

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