Sports Data Science Specialist

1 week ago

Koṭa, India beBeeArtificialIntelligence Full time

Job Title: AI/ML EngineerWe are seeking an experienced AI/ML Engineer to develop Sports Companion GPT - Aiko for sports applications.Key Responsibilities:• Design and develop AI models combining conventional ML techniques with generative AI for Cricket and Football applications.• Fine-tune pre-trained generative AI models using Cricket and Football-specific datasets.• Develop a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, 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 across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives.• Deploy models into production environments, preferably leveraging Azure cloud platforms, 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.The ideal candidate will have over 5 years of experience in AI/ML engineering, with significant expertise in building ML models and working with large datasets.Experience with fine-tuning generative AI models and familiarity with Azure cloud platforms is a plus but not mandatory.The preferred qualifications include experience fine-tuning large language models or generative AI for domain-specific applications, developing evaluation frameworks for generative AI models, and familiarity with Azure cloud services for model development and deployment.Knowledge of reinforcement learning or multimodal AI models and contributions to open-source AI/ML projects or published research in relevant fields are also desirable.

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