Design, develop, and deploy core machine learning models for analyzing player performance, including biomechanical analysis, shot trajectory prediction, energy transfer optimization, and cognitive performance assessment.
Develop and implement natural language processing (NLP) models to ingest, process, and understand external scientific research (sports biomechanics, ballistics, neurology). This includes building a system for summarizing research papers, extracting key insights, and creating a knowledge base.
Develop and implement personalization algorithms to tailor coaching recommendations based on individual athlete characteristics, performance history, and learning styles.
Integrate scientific research findings and sports science principles into the AI engine to ensure the accuracy and effectiveness of feedback and training recommendations.
Develop and implement algorithms for real-time data fusion from various sources, including video streams, wearable sensors (Apple Health, WHOOP, Oura), and environmental data.
Build and maintain a robust data pipeline for collecting, processing, and storing large datasets of player performance data, scientific literature, and environmental information.
Implement self-learning and continuous retraining mechanisms for AI models based on user performance and new scientific discoveries.
Develop AI-generated reports including biomechanical shot analysis, energy transfer metrics, and comparisons to elite athletes.
Create AI-powered training adjustments and personalized drill recommendations based on player performance, fatigue detection, and form deviations.
Collaborate with SMEs (Subject Matter Experts) in sports science and coaching to validate AI-generated feedback and recommendations.
Continuously research and evaluate new machine learning techniques and technologies to improve the platform’s performance and capabilities.
Participate in code reviews, testing, and deployment processes.
Required Skills and Qualifications
5+ years of experience in developing and deploying machine learning models in a production environment.
8+ years of experience in software development
Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, reinforcement learning, deep learning) and their applications.
Proficiency in programming languages such as Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn, Transformers).
Experience with natural language processing (NLP) techniques and libraries.
Experience with data processing and storage technologies (e.g., SQL, NoSQL databases, cloud computing platforms).
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
Preferred Skills and Qualifications
Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
Experience in the sports technology or related field.
Knowledge of sports biomechanics, physics, and neurology.
Experience with real-time data processing and analysis.
Familiarity with wearable sensor data and integration.
Experience with building and maintaining data pipelines.
Experience with cloud computing platforms (AWS, GCP, Azure).
Experience with LLM-based summarization and QA engines.
Experience with computer vision techniques and libraries (e.g., OpenCV).
Experience with user interface design and development.
