Job Title

Job Overview:We are seeking a Principal AI Engineer / AI System Architect with deep expertise in Computer Vision, Machine Learning, and Generative AI, capable of designing and owning end-to-end scalable AI systems from research to production. The role involves defining AI architecture and modeling strategy, integrating classical ML, deep learning, and Gen AI techniques (such as RAG, agents, and multimodal models), and ensuring solutions are production-ready, reliable, and aligned with business objectives. The candidate will provide technical leadership, guide AI system design decisions, and collaborate closely with cross-functional teams to deploy robust AI platforms at scale.Key Responsibilities:Architect and own end-to-end AI systems covering video/data analysis, model development, deployment, and monitoring. Design scalable AI architectures for real-time and batch processing use cases. Define modeling strategies across Computer Vision, classical ML, deep learning, and GenAI solutions. Lead the design and implementation of multimodal AI systems combining vision, language, and structured data. Design and implement RAG pipelines, AI agents, and hybrid approaches involving prompting, retrieval, and fine-tuning. Establish evaluation frameworks and metrics aligned with business and technical objectives. Guide MLOps practices including model versioning, monitoring, retraining, and performance tracking. Make architectural trade-offs across accuracy, latency, cost, scalability, and reliability. Ensure AI safety, governance, and responsible AI practices are embedded into system design. Collaborate with data engineering, platform, product, and business teams to align AI solutions with enterprise needs. Mentor senior engineers and data scientists, providing technical direction and long-term AI vision. Communicate complex AI concepts clearly to both technical and non-technical stakeholders.Skills and Qualifications:Strong expertise in Machine Learning, Deep Learning, and Computer Vision, with hands-on experience building and deploying enterprise-scale AI systems. Deep understanding of supervised, unsupervised, and reinforcement learning techniques, along with model evaluation, optimization, and performance trade-offs. Proven experience designing and implementing scalable AI architectures for real-time and batch processing use cases. Hands on experience in video and image processing, Object Detection and tracking, Human Pose & Biomechanics, Action Recognition, 3D Reconstruction and Synthetic Data Generation, And CUDA-accelerated filtering Advanced proficiency in Python and common ML frameworks (such as PyTorch, TEnsforflow, scikit-learn), along with strong data handling and feature engineering capabilities across structured and unstructured data. Experience in Edge based deployment on AI models ex. CoreML for iOS, and TensorFlow Lite (TFLite) for mobile deployment. Experience in Inference Optimization using NVIDIA TensorRT, OpenVINO, or TFLite for low-latency performance. Practical experience delivering end-to-end AI solutions, including Video/ Image data analysis, model training, deployment, monitoring, and continuous improvement. Strong understanding of MLOps practices, including model versioning, monitoring, retraining strategies, and handling data or model drift. Experience working with cloud platforms (AWS, Azure, or GCP) for AI/ML workloads and large-scale data processing. Hands-on exposure to Generative AI solutions, including RAG-based architectures, multimodal systems, and AI agents. Ability to define and apply evaluation frameworks for ML and GenAI solutions aligned with business objectives. Strong system design skills with the ability to balance accuracy, latency, cost, scalability, and reliability. Experience mentoring engineers and providing technical leadership across AI initiatives. Excellent communication skills to articulate complex technical concepts to both technical and non-technical stakeholders. Experience in Sports domain will be a plus.Educational Background:PhD or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Relevant certifications or research contributions in AI/ML are a strong plus.