AI / ML Engineer

Job Description

Below is a comprehensive job description tailored for an AI Engineer for our patented project, with an initial focus on cricket and badminton. This role is designed for someone who may not have direct sports officiating experience but comes from related fields (such as robotics, surveillance, autonomous systems, or sports analytics) and is eager to apply their expertise in a new domain. Job Overview As our AI/ML Engineer, you will be responsible for designing and prototyping the core machine learning architectures that drive our solution. You will collaborate directly with the founder to brainstorm, evaluate, and select the best approaches for computer vision, sensor fusion, and reinforcement learning applications in cricket and badminton. Given that this is a new domain, candidates with experience in adjacent areas (such as robotics, autonomous systems, sports analytics, surveillance, or IoT) are encouraged to apply. We value innovative problem solvers who can adapt their skills to meet our unique challenges. Key Responsibilities Architecture & Design: Propose and evaluate multiple AI/ML architectures suitable for real-time officiating tasks (object detection, event detection, trajectory prediction, and sensor fusion). Collaborate with the founder to select and iterate on the optimal architecture for our use case. Algorithm Development: Develop computer vision algorithms to detect and track critical objects (e.g., sports balls, players, court lines). Design and implement reinforcement learning (RL) models for dynamic PTZ camera control (tracking, panning, and zooming) to ensure the best camera viewpoints. Build predictive models for real-time decision-making (e.g., anticipating ball trajectories for no-ball calls, scoring events). Sensor Fusion: Integrate data from video feeds with auxiliary sensors (audio, IR, radar, etc.) to improve the accuracy and reliability of event detection. Optimize models for low-latency performance on edge devices. Prototyping & Testing: Rapidly prototype and validate AI/ML modules using real or simulated data. Work closely with the full-stack developer to integrate AI components into the broader software system. Documentation & Research: Document architecture decisions, model designs, and implementation details. Stay updated on recent research and advancements in computer vision, machine learning, and reinforcement learning, and apply relevant innovations to enhance the product. Collaboration: Participate in brainstorming sessions and technical reviews with the product management and development teams. Provide insights on potential improvements and scalability for the system as we expand from a prototype to a full-scale commercial product. Qualifications & Skill Sets Educational Qualifications: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related discipline with a focus on machine learning, computer vision, robotics, or data science. Technical Skills: Programming Languages: Proficiency in Python and familiarity with C++. Deep Learning Frameworks: Experience with TensorFlow, PyTorch, or similar frameworks. Computer Vision: Hands-on experience with OpenCV, YOLO, or other object detection and tracking libraries; strong knowledge of convolutional neural networks (CNNs). Reinforcement Learning: Understanding of RL concepts and experience with frameworks such as OpenAI Gym or similar; ability to prototype RL solutions for real-time control. Sensor Fusion: Familiarity with techniques to integrate and process multi-modal data (video, audio, IR, radar, etc.). Optimization for Real-Time Systems: Experience in tuning models and algorithms for low-latency, edge, or embedded deployment. Software Engineering: Ability to write clean, well-documented code and collaborate using version control systems (e.g., Git). Domain-Relevant Experience: While direct experience in sports officiating is not required, experience in adjacent fields such as: Sports Analytics: Building models for performance analysis or event detection in sports. Robotics/Autonomous Systems: Developing vision and control algorithms for real-time decision-making. Surveillance/IoT: Implementing sensor fusion techniques and real-time video analytics. Project or research experience that demonstrates your ability to solve complex problems in real-time environments is highly desirable. Soft Skills: Problem-Solving: Ability to work through challenging technical problems and innovate solutions. Collaboration: Excellent communication skills to articulate technical concepts to non-technical stakeholders and work effectively in a small, cross-functional team. Adaptability: Self-motivated and eager to learn new domains, with a proactive approach to overcoming technical challenges. Team Spirit: A willingness to contribute ideas, accept feedback, and continuously iterate on solutions. Why Join Us? Innovative Domain: Be at the forefront of merging AI with sports officiating and analytics—a field ripe for innovation. Collaborative Environment: Work directly with the founder and a lean, agile team, where your ideas directly influence the product’s direction. Growth Opportunity: Gain experience in building a product from concept to market, with room to grow as the company scales. Competitive Compensation: We offer a competitive salary with potential equity participation in a rapidly evolving startup.