4 Object Tracking Jobs

Are you ready to experiment, learn, and implement in the field of ML, Python, Computer Vision, hardware platforms like Jetson Nano and Raspberry Pi, and cloud services Join us on a new adventure where your expertise can revolutionize the dynamics of our organization. We believe in selection, not rejection, and we are excited to welcome you to our team. OptiSol is your destination for a stress-free and balanced lifestyle. We provide a nurturing environment where your career can flourish. As a certified GREAT PLACE TO WORK for 4 consecutive years, we value open communication, accessible leadership, diversity, and work-life balance with flexible policies. At OptiSol, you can thrive both personally and professionally. We are at the forefront of AI and innovation, shaping the future together. Join us on this journey of learning and growth. What we like to see in you: - Core Competencies: Programming, AI Expertise, IoT Hardware, Protocols (RTSP, TCP, MQTT, Modbus, UART), Leadership - Bachelor's/masters in computer science, ECE, or related fields - Expertise in Python and relevant ML frameworks (TensorFlow, PyTorch, OpenCV) - Strong understanding of neural networks, transfer learning, and optimization techniques - Proficiency with Jetson Nano, Raspberry Pi, Arduino, and related platforms - Familiarity with RTSP, TCP, MQTT, Modbus, UART - Proven experience in leading technical teams and managing projects What do we expect: - Hands-on experience with model quantization, multitask learning, and zero-shot fine-tuning - Familiarity with OCR and multimodal LLMs for different data types - Experience in API development using FastAPI and Django, plus Android AI apps - Knowledge of industrial cameras, motor drivers, and Ethernet switches - Proficiency in CUDA programming and GPU optimization What You'll Bring to the Table: - Lead a team of AI engineers and promote a creative and collaborative environment - Work with stakeholders to define project goals and milestones - Deliver high-quality AI-driven solutions on time - Tweak machine learning and computer vision algorithms for tasks like object detection - Deploy AI on edge devices like Jetson Nano or Raspberry Pi - Integrate AI models with electronics and solve hardware-software challenges - Manage AI services on cloud platforms (AWS, Azure, Google Cloud) - Test, validate, and document solutions following industry best practices Core benefits you'll gain: - Lead and inspire a team of engineers in a collaborative setting - Directly shape project goals and ensure project success - Gain hands-on experience in cutting-edge AI and computer vision applications - Dive into edge devices like Jetson Nano and Raspberry Pi - Manage AI services on cloud platforms securely and efficiently - Develop a well-rounded skill set in AI and hardware Join us as an OptiSolite and discover a fulfilling career with us. Explore life at OptiSol and learn more about our culture on our Insta Page.,

Vimaan is looking to onboard multiple Machine Learning Engineers in Bengaluru, India to drive the development of computer vision and machine learning algorithms to power our cutting-edge wall-to-wall warehouse inventory tracking and verification platform. This is a unique opportunity to exploit a treasure cove of unseen real-world data coming from a multi-camera perception system and develop large-scale computer vision and deep learning models to build a product that creates a disproportionate value for the warehouse industry. The role involves hands-on CV/ML software development and deployment from understanding the product requirements, defining Computer Vision functional specs to designing, developing, and deploying CV/ML models in production at scale. The ideal candidate for the Machine Learning Engineer position should have an MS in computer vision, machine learning, AI, applied mathematics, data science, or related technical fields, or a BS with 3+ years of experience in Computer Vision/Machine Learning. They should possess hands-on experience in developing new learning algorithms for computer vision tasks such as object detection, object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation, adversarial and generative models, as well as representational learning with varying amounts of data. Knowledge of current deep learning literature and the mathematical foundations of machine learning is essential. Experience with popular object detection frameworks such as YOLO, SSD, or Faster R-CNN is considered a plus. The candidate should have the ability to train and debug deep learning systems, gain deep insights into data characteristics, and map those to appropriate model architectures. Experience working with inputs from multiple cameras and input modes is advantageous, as is experience in AI Infrastructure, Machine Learning Accelerators, On-Device Optimization, and training and deploying deep learning models on GPU-accelerated platforms. Strong programming skills with Python and experience with ML/DL frameworks like Tensorflow, Pytorch, etc., are required. Prior experience in deploying machine learning models in production environments, working with cloud platforms (e.g., AWS, Azure, Google Cloud), and familiarity with data pre-processing, augmentation, and visualization tools and libraries are necessary. The ideal candidate should be highly motivated, passionate, possess a strong work ethic, and be able to work effectively in a team or independently under supervision in a matrix management environment. Effective communication skills, problem-solving abilities, attention to detail, and a passion for staying at the forefront of technology advancements in machine learning and computer vision are key attributes. They should be able to work in a fast-paced, high-pressure startup environment, adapt to rapidly changing requirements, and convey complex technical concepts to non-technical stakeholders. The Machine Learning Engineer will be responsible for researching, designing, and developing machine learning algorithms and models for various tasks of detection, recognition, and classification for warehouse inventory management. They will implement and optimize deep learning architectures, explore techniques like transfer learning and data augmentation, guide annotation teams, curate and pre-process annotated datasets, collaborate with MLOps for integrating machine learning models into production systems, and conduct thorough performance analysis and evaluation of models using appropriate metrics and tools. It is essential for the Machine Learning Engineer to stay up-to-date with the latest advancements in machine learning and computer vision research and integrate relevant findings into the solutions developed at Vimaan. ABOUT VIMAAN Headquartered in Silicon Valley, with team members around the world, Vimaan is comprised of computer vision and hardware technologists, as well as warehousing domain experts with a successful history in technology startups. Vimaan's primary mission is to deliver computer vision and machine learning solutions to solve long-standing inventory visibility, accuracy, and quality challenges in the supply chain.,

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.,

About the Role: Looking for a highly experienced Computer Vision Specialist / AI Engineer to join our dynamic team. The ideal candidate will have a proven track record of delivering real-world computer vision and deep learning solutions, particularly in smart monitoring and edge & cloud AI applications. This role demands deep technical expertise in designing and deploying vision-based solutions such as object detection, object tracking, facial recognition, behavioral analysis, ANPR and OCR. You will lead the development and deployment of scalable, production-grade AI systems. Lead the architecture, development, and deployment of computer vision systems from concept to production. Develop and optimize advanced vision algorithms and deep learning models for real-time performance. Optimize AI/ML models for deployment across edge, cloud, and hybrid environments using tools like TensorRT, TFLite, OpenVINO, and ONNX. Collaborate with hardware and software engineering teams to ensure system-wide performance optimization. Conduct thorough testing, benchmarking, and performance tuning of models and systems. Required Skills & Experience: 25 years of hands-on experience in Computer Vision, Deep Learning, and AI model deployment. Strong proficiency in Python , with production-level experience in writing clean, modular, and scalable code. Familiar with frameworks and tools such as OpenCV, TensorFlow, PyTorch, YOLO, MediaPipe, Dlib. In-depth knowledge of: Convolutional Neural Networks (CNNs) o Object detection and tracking o Facial recognition techniques o Video-based behavioral analysis RTSP streaming, CCTV camera systems, NVR/DVR integration Deployment experience on platforms including: Edge devices (NVIDIA Jetson, Raspberry Pi, Coral Edge TPU) o Cloud (AWS/Azure/GCP) with containerization tools (Docker) Strong understanding of MLOps tools and workflows, including model tracking, data versioning, monitoring, and retraining. Nice to Have: Familiar with LLM and Vision Language Models