5 Yolov8 Jobs

Joining Gadgeon offers a dynamic and rewarding career experience that fosters both personal and professional growth. Our collaborative culture encourages innovation, empowering team members to contribute their ideas and expertise to cutting-edge projects. As a Computer Vision & Edge AI Engineer at Gadgeon, you will be responsible for developing AI solutions for visual understanding, document parsing, and multimodal processing. In this role, you will enable new use cases beyond text by integrating image, OCR, and edge-deployable AI capabilities. Key Duties/ Responsibilities: - Develop OCR and image processing pipelines using tools like OpenCV, Tesseract, or AWS Textract. - Train and fine-tune visual models such as YOLOv8, SAM, CLIP for internal Proof of Concepts (PoCs). - Integrate visual AI modules into end-to-end workflows used by LLMs or agents. - Optimize models for edge deployments using ONNX, TensorRT, or TFLite. - Collaborate with backend and AI teams for data structure alignment. Leadership Skills: - Self-driven in visual AI exploration. - Effective in prototyping and cross-functional collaboration. - Ability to demonstrate impact through PoCs. Required Technical Skills: - Proficiency in OpenCV, YOLOv8, SAM, BLIP2, Tesseract. - Experience with ONNX, TensorRT, AWS Panorama, Jetson Nano. - Strong programming skills in Python, PyTorch/TensorFlow, edge deployment toolchains. - Familiarity with visual AI stacks like YOLOv8, SAM, CLIP, or equivalent. - Capability to structure visual outputs for downstream agent or LLM processing. Qualification: - Bachelors or Master's degree in Computer Science, AI/ML, Data Science, or related fields. Experience: - Minimum of 4 years of relevant experience in the field.,

computer vision or deep learning roles industrial/safety inspection datasets (e.g., PPE detection, visual defect classification). Familiarity with MLOps tools like MLflow, DVC, or ClearML. ONNX, TensorRT, OpenVINO

As a Computer Vision Intern, you will be responsible for assisting in building and refining the image recognition pipeline. Your role will involve tasks such as dataset management, image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is completed, you will gain hands-on experience in model training, augmentation, and evaluation, directly contributing to our production-ready pipeline. Your responsibilities will include organizing, cleaning, and preprocessing large-scale retail image datasets, validating and managing annotations using tools like Roboflow, CVAT, or LabelImg, applying augmentation techniques, preparing datasets for training, supporting in training YOLOv5/YOLOv8-based models on custom datasets, running model evaluations, collaborating with the product team to enhance real-world inference quality, and documenting the dataset pipeline while sharing insights to improve data quality. We are looking for individuals who have a basic understanding of Computer Vision concepts such as Object Detection and Classification, familiarity with Python libraries like OpenCV, Pandas, NumPy, knowledge of image annotation tools like Roboflow, LabelImg, CVAT, and the ability to manage and organize large datasets. Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine-tuning), exposure to image augmentation techniques like Albumentations, understanding of retail/commercial shelf datasets or product detection problems, and previous internship or project experience in computer vision would be considered advantageous for this role.,

We are looking for a highly experienced Senior AI/ML Engineer with a strong background in cloud infrastructure and IoT to join our dynamic team in Ahmedabad. As an ML Engineer/MLOps Engineer, your primary responsibility will be to lead the design, development, and deployment of AI/ML solutions on cloud platforms, integrate IoT technologies, and drive innovation in intelligent systems. Your role will involve leading the end-to-end development and deployment of AI/ML solutions on cloud platforms such as AWS for applications like predictive analytics, anomaly detection, and intelligent automation. You will also be responsible for integrating IoT sensors, devices, and protocols like MQTT into AI/ML solutions to enable intelligent decision-making, remote monitoring, and control in IoT environments. Additionally, you will architect and optimize cloud infrastructure for AI workloads, design data pipelines for IoT data ingestion, and train machine learning models for various tasks using state-of-the-art algorithms and frameworks like PyTorch. Collaboration with cross-functional teams, including data scientists, software engineers, and product managers, is essential to define project requirements, develop prototypes, and deliver scalable AI/ML solutions that align with business objectives. You will need to implement algorithms and models proficiently using programming languages like Python, R, or Java and leverage relevant libraries and frameworks for computer vision tasks. Furthermore, you should have a Bachelor's or Master's degree in Computer Science, Engineering, or related field, along with 3-5 years of proven experience as an AI/ML Engineer. Strong programming skills in Python, familiarity with AI/ML libraries/frameworks, IoT development, containerization, and serverless computing are crucial requirements for this role. A deep understanding of machine learning algorithms, model training, validation, and deployment best practices is also essential. If you are willing to relocate to Ahmedabad and meet the educational and experience requirements mentioned above, we encourage you to apply for this full-time ML Engineer/MLOps Engineer position.,

Experienced AI/ML Engineer to lead the design, training, and deployment of an integrated multi-model AI system for asset detection, activity monitoring, environmental analysis, and threat prediction using satellite and aerial imagery. The role will involve building specialized deep learning models (YOLOv8, U-Net, RetinaNet, LSTM, ResNet50, GAN, BERT, XGBoost) and integrating them into an operational, agentic AI framework capable of delivering real-time intelligence and early warnings to support defense and security operations. Role & responsibilities Preferred candidate profile Bachelors/Masters/PhD in Computer Science, AI, Data Science, Remote Sensing, or related field. 2-5 years of hands-on experience developing and deploying deep learning models for imagery analysis. Proven experience with YOLOv8, RetinaNet, U-Net, LSTM, ResNet, GANs, BERT, XGBoost . Strong Python skills with PyTorch and/or TensorFlow . Proficiency with geospatial libraries: GDAL, Rasterio, GeoPandas, OpenCV, Shapely . Experience with multi-temporal change detection and time-series modeling. Familiarity with cloud environments (AWS, Azure, GCP) and containerization (Docker/Kubernetes). Understanding of SAR, multispectral, and hyperspectral imagery. Excellent grasp of MLOps and model lifecycle management. Preferred Skills Experience with defense, security, or intelligence projects. Knowledge of satellite tasking APIs (Copernicus, Planet, Maxar). Onboard/edge AI experience (e.g., NVIDIA Jetson, CubeSat). Strong skills in building rule-based AI systems and integrating them with ML predictions.