Job
Description
As the AI Model Development & Deployment Lead, your primary responsibility will be to design and implement cutting-edge computer vision models for various tasks such as object detection, tracking, segmentation, and action recognition. You should have expertise in architectures like YOLO (v4, v5, v8), Vision Transformers, Mask R-CNN, Faster R-CNN, LSTMs, and Spatio-Temporal Models for in-depth image and video analysis. It will be crucial to contextualize the models for challenging scenarios like poor detection due to occlusion or small, fast-moving objects by training them on diverse situations. Your role will involve identifying reasons for suboptimal model performance and developing a scalable computer vision layer adaptable to different environments. Collaborating with data scientists using frameworks like TensorFlow and Pytorch, you will drive impact across key KPIs and optimize models for real-time inference through techniques such as quantization, pruning, and model distillation. In the realm of Reinforcement Learning & Model Explainability, you will be tasked with developing and integrating reinforcement learning models to enhance decision-making in dynamic AI environments. This will involve working with Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), A3C, SAC, and other RL techniques. Furthermore, you will explore explainability methods such as SHAP, LIME, and Grad-CAM to ensure transparency and interpretability of AI-driven decisions. Additionally, engineering context-aware features from video sequences to extract temporal and spatial insights for improved model explainability and decision accuracy will be part of your responsibilities. Leading the charge in creating a Scalable Data Model for AI Model Training Pipelines, you will oversee the end-to-end data preparation process, including data gathering, annotation, and quality review before training data utilization. The focus will be on enhancing the quality and volume of training data continuously to boost model performance iteratively. Your expertise in planning the data model for future scalability, with the ability to incorporate new data elements in a modular manner, will be essential. Key Technical Skills required for this role include a proven track record in delivering AI products, hands-on experience with advanced AI models, proficiency in managing and mentoring a small team of data scientists, expertise in AI/ML frameworks like TensorFlow, PyTorch, and Keras, effective collaboration with cross-functional teams, and strong problem-solving skills in image and video processing challenges. Nice to have skills include a mindset for experimentation, iterative improvement, and testing to enhance model performance continually, staying updated with the latest AI research, and balancing experimentation with timely product delivery. Collaboration with engineering and product teams to align AI solutions with product goals and deployment of AI models into production are crucial aspects. Additionally, leadership in guiding and mentoring a team of AI scientists, taking ownership of product KPIs related to AI models, and fostering an AI-first culture focused on innovation and continuous improvement will be part of your role.,
