7 Pose Estimation Jobs

Company Description Shoplinky is a platform that enables content creators to monetize their content through personalized storefronts, AI-driven brand collaborations, seamless monetization options and social media automations. For brands, Shoplinky offers AI-powered features to integrate products into organic content that drives sales and builds trust. Shoplinky aims to create a community where creators, brands, and audiences collaborate to make commerce more engaging and rewarding. Role Responsibilities Participate in developing computer vision models for object detection, scene segmentation, and tracking in video content Implement motion-aware logic for placing 3D objects accurately in dynamic video scenes Build video processing workflows for analyzing frames and applying virtual product overlays Contribute to NLP and recommendation models for suggesting relevant products based on content context Collaborate with 3D and platform teams to support rendering and positioning of assets in real time Engage in testing, debugging, and optimizing AI models. Participate in model evaluation and dataset handling for iterative improvements Work closely with developers and the team Qualifications Foundational knowledge of Computer Vision, 3D geometry and motion tracking Exposure to object detection, pose estimation, or scene understanding (OpenCV, Mediapipe, etc.) Familiarity with 3D formats or engines (e.g., GLTF, Three.js, Unity, Blender) Proficient in Python and basic experience with ML libraries (e.g., PyTorch, TensorFlow) Bonus: exposure to NeRFs, SLAM, or AR/VR projects Bachelors degree in Computer Science, AI, or related field (or pre-final year student with bold understanding about the skillset mentioned) Experience in integrating Generative AI Models. Enthusiastic learner with strong problem-solving skills and interest in content + commerce AI Interested candidates, please share your resumes at [HIDDEN TEXT] Show more Show less

Are you passionate about computer vision, augmented reality, and deep learning Join us as an intern and gain hands-on experience in a fast-growing company where you'll contribute directly to cutting-edge projects. We are seeking a dedicated individual to assist in the development and training of a Virtual Try-On (VTO) system for wristwatches. About Us: We are disrupting the interior shopping business by adding another dimension to the sales process through augmented reality (AR) and 3D visualization. Our fundamental drive is seeing is believing, and that's exactly what we're doing with Web AR. We're helping clients make more informed decisions by allowing them to visualize products in real-world environments, a shift we call smart shopping. As we experience significant growth, we're expanding our team with talented individuals who have an eye for detail and the ability to thrive under deadlines. You'll work closely with our production manager and 3D modelers, ensuring that the products we create in AR correlate fully with our clients" expectations. Responsibilities: - Collaborate with our engineering and production team to build and refine VTO models. - Assist in the development and training of machine learning models, particularly in computer vision applications. - Work with 3D visualization to ensure the accurate rendering and alignment of models in AR environments. - Optimize model performance for real-time user interactions. Required Skills: - Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch). - Experience with computer vision libraries (e.g., OpenCV, Mediapipe). - Knowledge of 3D geometry, pose estimation, and object detection. - Familiarity with augmented reality development tools and frameworks. - Strong understanding of convolutional neural networks (CNNs) and model training techniques. - Experience working with datasets for image processing and custom landmark detection. - Attention to detail and ability to work collaboratively under deadlines. Preferred Qualifications: - JavaScript experience, particularly for integrating AR/VR solutions into web environments. - Prior experience in building virtual try-on (VTO) systems or related AR applications. - Familiarity with real-time inference optimization and model compression techniques. - Knowledge of wrist landmark detection and training custom models for body part tracking. What We Offer: - An opportunity to work in a dynamic, growth-driven environment. - Hands-on experience with innovative technology in augmented reality. - Mentorship from experienced professionals in computer vision and AR. - A platform to sharpen your skills and contribute to exciting real-world applications. THIS IS AN UNPAID INTERNSHIP THAT OFFERS AN EXCELLENT LEARNING OPPORTUNITY WITH REAL-WORLD IMPACT AND EXPOSURE TO CUTTING-EDGE TECHNOLOGY. ONLY APPLICANTS WHO CAN WORK ONSITE SHOULD APPLY.,

Location: Remote | CTC: 5,00,000-7,00,000 LPA + ESOPs About Us : We&aposre on a mission to revolutionize sports analytics by integrating cutting-edge AI into real-time and post-match video analysis. Our platform delivers powerful insights to enhance athlete performance, optimize coaching strategies, and engage fans like never before. Join us at the intersection of technology and athletic excellence. Role Overview : As an AI Sports Analyst / Computer Vision Engineer , you&aposll play a pivotal role in our technology team, developing intelligent systems that analyze sports video footage to uncover performance metrics, tactical patterns, and game-changing insights. Your innovations will help athletes train smarter, enable coaches to make data-driven decisions, and transform how fans connect with the game making a real impact on the future of sports. Job Responsibilities As our AI Engineer, you will: ? Build and optimize computer vision models to detect and track players, ball, referee, and other key entities in sports footage ? Develop event recognition models ? Implement pose estimation and action recognition algorithms for performance analytics ? Work with multi-camera setups to perform 3D player reconstruction and spatial analysis ? Deploy models in real-time pipelines and optimize for low-latency inference ? Integrate AI pipelines with front-end visualization dashboards ? Collaborate with frontend/backend devs, data annotators, and sports analysts ? Stay up to date with state-of-the-art research in vision-based sports analytics Preferred Skills : ?? Real-time inference pipeline design ? Prior work on sports ????? Familiarity with multi-view 3D reconstruction ???? Pose estimation or skeletal keypoint tracking ???? Background in Reinforcement Learning for player movement prediction (optional) ???? Research publications or GitHub repos in sports AI ???? Experience with MLOps tools: Weights & Biases, MLflow, DVC Show more Show less

At Peak Medical, our mission is to make rehabilitation smarter, more accessible, and deeply human. We are building BIBO, a clinically validated, AI-powered platform that helps people recover from surgery and manage pain safely at home, mirroring the care of a physiotherapist. It is the first product to go through a high regulatory class to be able to instruct patients at home, with live, clinical advice. This is a significant advancement in Healthcare access. We are a small, smart, agile team located across Australia and India, dedicated to building the next generation of digital musculoskeletal care. Our focus is on providing real-time insights and motion analysis that lead to recovery, reducing the reliance on clinic visits. Our pilot partners and end customers span across Australia and India. We are currently seeking a Senior Computer Vision Engineer with a minimum commitment of 4 years to join our team. As a key member, you will be responsible for leading the development and refinement of our AI motion tracking pipeline, with specific expertise in pose estimation and mobile deployment. This role offers the opportunity to work closely with our product and clinical teams and be part of a passionate and focused team. Key Responsibilities: - Architect and develop real-time pose estimation solutions using tools like MediaPipe and BlazePose. - Build, test, and refine computer vision models integrated into mobile workflows. - Work across platforms such as Flutter, MediaPipe, TFLite, and Python-based toolkits. - Optimize models for low-latency inference on mobile devices. - Lead and implement product architecture. - Conduct research and development on motion accuracy, error handling, and safety thresholds. - Collaborate with cross-functional teams across different time zones (Australia/India). - Contribute to product strategy and user-centric design for at-home care. - Perform model optimization (quantization, pruning) for real-time performance on mobile. Requirements: - 6+ years of experience in AI/ML with a focus on Computer Vision. - Experience in Healthcare, Fitness, Physiotherapy, Medical, or Movement Industries. - Proven ability to build, deploy, and iterate CV models in production environments. - Expertise in MediaPipe, TFLite, EDGE computing, real-time model inference, and pose estimation models. - A builders mindset with a passion for leading CV development in a mission-driven startup. - Experience working with mobile-first health tech or real-time movement data is a plus. - Proficiency in Flutter/Dart, Kotlin, Swift, TensorFlow, and Python. - Comfortable working both independently and collaboratively in a small team. - Experience fine-tuning pre-trained models and deploying them in production apps. - Ability to devise a data set training strategy to enhance model performance. - Experience with AI-powered data analytics and visualization. This position offers great remuneration and ESOP. Join us on this journey where your vision can drive the movement that disrupts Healthcare. Apply now to be part of our team at Peak Medical.,

You will be responsible for building and maintaining backend logic in PHP (CodeIgniter) and Python (Flask, FastAPI, etc.). Additionally, you will design and implement computer vision workflows using tools such as OpenCV, YOLOv8, MediaPipe, or equivalent tools. Your tasks will involve working with image/video inputs to perform real-time detection of various elements like faces, objects, license plates, hazards, etc. Furthermore, you will integrate with third-party APIs, IoT devices, and edge-based platforms such as Jetson Nano, Raspberry Pi. It will be crucial for you to optimize vision pipelines for enhanced performance, accuracy, and reliability. Your role will also include deploying and enhancing full-stack solutions. To excel in this position, you should hold a Bachelor's degree and possess a minimum of 3 years of hands-on experience with PHP and Python. Demonstrated expertise with OpenCV and YOLO (v5/v8 preferred) is essential. A strong understanding of image processing, video analytics, and real-time detection is required. Proficiency in Linux environments, Git, and REST APIs is expected. Familiarity with edge AI, ONNX, or experience in deploying models on Jetson/Raspberry Pi will be advantageous. Knowledge of object tracking, counting, pose estimation, etc., will also be beneficial for this role.,

Join the leader in entertainment innovation and help design the future at Dolby. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you will see and hear the results of your work everywhere, from movie theaters to smartphones. Dolby continues to revolutionize how people create, deliver, and enjoy entertainment worldwide. To achieve this, Dolby seeks the absolute best talent. Dolby is big enough to provide all the resources you need and small enough so you can make a real difference and earn recognition for your work. Dolby offers a collegial culture, challenging projects, excellent compensation and benefits, and a Flex Work approach that truly supports where, when, and how you do your best work. Your role at Dolby will involve bringing your experience in geometry/texture processing computer vision tasks and deep learning technology to the team. As a prerequisite, you must have proven knowledge of geometry/texture processing, image/video enhancement and restoration, computer graphics, and deep learning. Your solid understanding of the trade-offs between computational complexity and achieved performance of different implementations will guide you in making decisions. You will be responsible for researching and developing new neural network architectures, training methods, representation, and processing algorithms in the modern computer vision domain. You are expected to have an in-depth understanding of the key processes in computer vision and extensive experience in developing architectures, low-level computer vision tasks, geometry/texture representation and processing, pose estimation and deformation, as well as dynamic 3D object modeling/representation/processing algorithms with deep learning to enhance the performance of computer vision tasks. You will join a highly skilled and motivated team dedicated to researching and developing advanced computer vision and processing technologies to enhance the end-user experience. Your responsibilities will include working with a general understanding of competitive technologies in the area of focus, understanding the system context in which new technologies will be used, and the requirements that the technology must fulfill for success. You will create early-stage conceptual models that demonstrate feasibility and document and present new architectures and algorithms in various forms, such as technical white papers and internal meetings. Maintaining the highest technical and moral integrity for Dolby in the workplace and marketplace is essential. Skills, Education, and Experience Required: - Ph.D. degree in electrical engineering, computer engineering, or computer science. - Minimum of 3 years of experience in developing algorithms for geometry representation learning (mesh, point cloud, etc), deep learning, computer vision, and computer graphics. - Proficiency in Matlab, C/C++, OpenCV, and Python (Tensorflow/Pytorch) programming applied to computer vision is required. - Strong background in the latest AI technologies and their applications to image research. - Self-motivated, quick learner, and strong team player with the ability to work with minimal supervision. - Excellent written and verbal communication skills. - Highly desirable to have one or more of the following: - Experience in filing patents for newly developed technologies. - Hands-on experience in applying Computer Vision and Machine Learning algorithms to real-world problems. - Proven track record of successful research accomplishments, published papers, and/or patent applications in the field of video encoding and processing. LI-SB1,

Job Summary: We are seeking a passionate and technically skilled AI / ML Engineer with 2+ years of hands-on experience in Computer Vision and Generative AI (GenAI). This role involves building and optimizing advanced visual intelligence systems leveraging PyTorch, OpenCV, transformers, and diffusion models. The ideal candidate will have experience in areas such as image segmentation, pose estimation, video inpainting, and synthetic data generation, along with exposure to LLM-prompt integration and datasets like DeepFashion2 and COCO. Key Responsibilities: Develop and deploy advanced computer vision models for tasks such as image segmentation, pose estimation, and video manipulation. Implement and experiment with Generative AI techniques, including diffusion models, GANs, and video inpainting. Leverage PyTorch, OpenCV, and modern deep learning frameworks to build scalable vision pipelines. Integrate LLM-based prompting into visual workflows and multimodal applications. Utilize datasets such as DeepFashion2, COCO, and custom synthetic datasets for model training and validation. Optimize model inference for performance, latency, and resource efficiency in production environments. Collaborate with data scientists, product engineers, and designers to deliver intelligent visual features in end-user applications. Qualifications: 2+ years of experience in machine learning and computer vision. Proficiency with PyTorch, OpenCV, and relevant deep learning libraries. Hands-on experience with image segmentation, pose estimation, or video-based vision tasks. Understanding of diffusion models, GANs, and transformer-based architectres. Knowledge of LLM prompt engineering and multimodal integration. Experience working with structured datasets like COCO and DeepFashion2. Strong debugging, analytical, and performance optimization skills. Preferred Qualifications : Experience in synthetic data generation and domain-specific data augmentation. Familiarity with model quantization, pruning, or other inference optimization techniques. Exposure to MLOps tools and cloud-based model deployment (e.g., AWS Sagemaker, GCP AI Platform). Contributions to open-source projects or published research in computer vision or generative models. Location: Pan- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai