AI Engineer

As an AI/ML Engineer at our company, your primary responsibility will involve designing and prototyping core machine learning architectures to drive our solution. You will work closely with the founder to brainstorm and select the best approaches for computer vision, sensor fusion, and reinforcement learning applications specifically tailored for cricket and badminton. We are particularly interested in candidates with experience in related areas such as robotics, autonomous systems, sports analytics, surveillance, or IoT due to the unique nature of this new domain. We value creative problem solvers who can adapt their skills to meet the challenges presented in our project. Your key responsibilities will include proposing and evaluating AI/ML architectures for real-time officiating tasks, developing computer vision algorithms for object detection and tracking, designing reinforcement learning models for dynamic camera control, and building predictive models for real-time decision-making. Additionally, you will be integrating data from various sensors to enhance event detection accuracy, optimizing models for low-latency performance, and prototyping AI/ML modules using real or simulated data. You must also document architecture decisions, model designs, and implementation details, while staying updated on recent research and advancements in computer vision, machine learning, and reinforcement learning to enhance our product. Collaboration is essential, as you will participate in technical reviews, provide insights on system improvements, and work closely with the full-stack developer to integrate AI components into the software system. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science, Electrical Engineering, or a related discipline with a focus on machine learning, computer vision, robotics, or data science. Proficiency in Python and familiarity with C++, experience with deep learning frameworks such as TensorFlow or PyTorch, hands-on experience with computer vision libraries, and understanding of reinforcement learning concepts are required technical skills. Familiarity with sensor fusion techniques, optimization for real-time systems, and software engineering practices is also expected. While direct experience in sports officiating is not mandatory, experience in fields like sports analytics, robotics, surveillance, or IoT will be advantageous. Soft skills such as problem-solving abilities, effective collaboration, adaptability, and team spirit are highly valued in our team. Join us to be part of an innovative domain that merges AI with sports officiating and analytics, work in a collaborative environment directly influencing the product's direction, gain growth opportunities as the company scales, and receive competitive compensation with potential equity participation in a rapidly evolving startup.,