AI/ML Specialist

AI/ML SpecialistWe are looking for a skilled AI/ML engineer to join our team and work on the development of Sports Companion GPT - Aiko, a cutting-edge sports analytics platform.The ideal candidate will have extensive experience in building and optimizing machine learning models, with a strong focus on generative AI techniques. They will be responsible for designing and developing AI models for Sports Companion GPT - Aiko, combining conventional machine learning algorithms with generative AI architectures.Key Responsibilities:Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications.Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports.Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications.Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models.Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases.Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications.Collaboration: Work with sports analysts, data engineers, and domain experts across different regions to incorporate domain knowledge into Aiko and align with business objectives.Deployment & Optimization: Deploy models into production environments, preferably leveraging cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications.Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks.Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing.Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs.Qualifications:5+ years in AI/ML engineering, with significant experience in conventional ML.Proven expertise in building ML models (e.g., Scikit-learn, XGBoost).Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory.Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory.Technical Skills:Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs).Experience with data preprocessing, feature engineering, and handling large datasets.Familiarity with cloud platforms for model training and deployment, with cloud experience as a strong plus.Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines.Experience with computer vision, natural language processing, or text generation is a plus.Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required.