10 Dlib Jobs

Technology->Artificial Intelligence->Computer Vision Job Overview: As a Lead Computer Vision Engineer, you will lead the development and deployment of cutting-edge computer vision models and solutions for a variety of applications including image classification, object detection, segmentation, and more. You will work closely with cross-functional teams to implement advanced computer vision algorithms, ensure the integration of AI solutions into products, and help guide the research and innovation of next-generation visual AI technologies. 2. Technical Skills: Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, or other deep learning libraries. Computer Vision Tools: Expertise in OpenCV, Dlib, and other image processing libraries. Model Deployment: Experience deploying models to production using platforms such as AWS, Google Cloud, or NVIDIA Jetson (for edge devices). Algorithms: Strong understanding of core computer vision techniques like image classification, object detection (YOLO, Faster R-CNN), image segmentation (U-Net), and feature extraction. Programming Languages: Proficient in Python, C++, and other relevant programming languages for computer vision tasks. Data Handling: Experience working with large datasets, data augmentation, and preprocessing techniques. Optimization: Skills in model optimization techniques such as pruning, quantization, and hardware acceleration (e.g., using GPUs or TPUs). trong working experience in Agile environment - Experience working and understanding of ETL / ELT, Data load process - Knowledge on Cloud Infrastructure and data source integrations - Knowledge on relational Databases - Self-motivated, be able to work independently as well as being a team player - Excellent analytical and problem-solving skills - Ability to handle and respond to multiple stakeholders and queries - Ability to prioritize tasks and update key stakeholders - Strong client service focus and willingness to respond to queries and provide deliverables within prompt timeframes.

Job Title: AI Developer – Computer Vision & ML Location: Coimbatore Company: Vpm Info Tech Experience: 1-3 years (Freshers with strong project portfolios may apply) Employment Type: Full-Time Job Description: We are seeking a skilled AI Developer with hands-on experience in computer vision and machine learning to develop intelligent surveillance systems. The role involves implementing and optimizing modules such as face detection for attendance , vehicle and number plate recognition , people counting , and motion detection using modern AI frameworks and libraries. Key Responsibilities: Face Detection + Attendance System: Build real-time face recognition systems using OpenCV, face_recognition, dlib, and manage attendance logs with SQLite3. Vehicle Detection + Number Plate Recognition: Develop vehicle detection and number plate OCR using Ultralytics (YOLOv8), EasyOCR, PyTesseract, OpenCV, and store data in MySQL. People Counting System: Implement people counting with tracking using YOLOv8, Deep SORT, Flask, OpenCV, and NumPy.Create motion detection modules using OpenCV, imutils, and NumPy.Integrate Google Cloud Vision API and custom OCR logic for advanced document/image analysis. Motion Detection: Cloud & OCR Integration: Collaborate with the backend team to ensure smooth data flow and API integrations. Optimize models and pipelines for real-time edge deployment (Raspberry Pi, Jetson Nano preferred). Required Skills: Proficiency in Python with libraries like OpenCV, NumPy, Flask, imutils, and threading. Experience with deep learning frameworks: Ultralytics YOLO, face_recognition, dlib. OCR tools: EasyOCR, Tesseract, Google Cloud Vision API. Databases: SQLite3, MySQL. Strong understanding of computer vision algorithms and real-time video processing. Preferred Qualifications: B.E/B.Tech/M.Sc in Computer Science, AI, Data Science, or related field. Knowledge of Docker, Git, and RESTful API design. Job Type: Full-time Pay: ₹15,000.00 - ₹35,000.00 per month Schedule: Day shift Supplemental Pay: Performance bonus Yearly bonus Work Location: In person

Company Description TrueFan uses proprietary AI technology to connect fans and celebrities and is now focused on revolutionizing customer-business interactions with AI-powered personalized video solutions. Our platform enables brands to create unique, engaging video experiences that drive customer loyalty and deeper connections. Company Overview We are a cutting-edge AI company focused on developing advanced lip-syncing technology using deep neural networks. Our solutions enable seamless synchronisation of speech with facial movements in videos, creating hyper-realistic content for various industries such as entertainment, marketing, and more. Position : MLOps Engineer We are looking for a talented and motivated MLOps Engineer to join our team. The ideal candidate will play a crucial role in managing and scaling our machine learning models and infrastructure, enabling seamless deployment and automation of our lip-sync video generation systems. Key Responsibilities Model Training/Deployment Pipelines and Monitoring : Design, implement, and maintain scalable and automated pipelines for deploying deep neural network models. Monitor and manage Production models, ensuring high availability, low latency, and smooth performance. Automate workflows for data preprocessing (face alignment, feature extraction, audio analysis), model retraining, and video generation. Implement Logging, Tracking, and Monitoring Systems to ensure data integrity and visibility into the model lifecycle. Infrastructure Management Build and manage cloud-based infrastructure (AWS, GCP, or Azure) for efficient model training, deployment, and data storage. Collaborate with DevOps to manage containerization (Docker, Kubernetes) and ensure robust CI/CD pipelines using github and jenkins for model delivery. Monitor resource for GPU/ CPU-intensive tasks like video processing, model inference, and training using Prometheus , Grafana, alert manager, ELK stack. Collaboration Work closely with ML engineers to integrate models into production pipelines. Provide tools and frameworks for rapid experimentation and model versioning. Required Skills Basic Python Strong experience with cloud platforms (AWS, GCP, Azure) and cloud-based machine learning services. Expert knowledge of containerization technologies (Docker, Kubernetes) and infrastructure-as-code (Terraform, CloudFormation) Have understanding of Deployment of both synchronous and asynchronous API using Flask, Django, Celery, Redis, RabbitMQ , Kafka Deployed and Scaled AI/ML in Production. Familiarity with deep learning frameworks (TensorFlow, PyTorch). Familiarity with video processing tools like FFMPEG and Dlib for handling dynamic frame data. Basic understanding of ML models Preferred Qualifications Experience in image and video-based deep learning tasks. Familiarity with media streaming and video processing pipelines for real-time generation. Experience with real-time inference and deploying models in latency-sensitive environments. Strong problem-solving skills with a focus on optimising machine learning model infrastructure for scalability and performance (ref:hirist.tech)

Company Description TrueFan uses proprietary AI technology to connect fans and celebrities and is now focused on revolutionizing customer-business interactions with AI-powered personalized video solutions. Our platform enables brands to create unique, engaging video experiences that drive customer loyalty and deeper connections. Job Description DevOps with MLOps Engineer Company Overview We are a cutting-edge AI company focused on developing advanced lip-syncing technology using deep neural networks. Our solutions enable seamless synchronisation of speech with facial movements in videos, creating hyper-realistic content for various industries such as entertainment, marketing, and more. Position: MLOps Engineer We are looking for a talented and motivated MLOps Engineer to join our team. The ideal candidate will play a crucial role in managing and scaling our machine learning models and infrastructure, enabling seamless deployment and automation of our lip-sync video generation systems. Key Responsibilities Model Training/Deployment Pipelines and Monitoring: Design, implement, and maintain scalable and automated pipelines for deploying deep neural network models. Monitor and manage Production models, ensuring high availability, low latency, and smooth performance. Automate workflows for data preprocessing (face alignment, feature extraction, audio analysis), model retraining, and video generation. Implement Logging, Tracking, and Monitoring Systems to ensure data integrity and visibility into the model lifecycle. Infrastructure Management: Build and manage cloud-based infrastructure (AWS, GCP, or Azure) for efficient model training, deployment, and data storage. Collaborate with DevOps to manage containerization (Docker, Kubernetes) and ensure robust CI/CD pipelines using github and jenkins for model delivery. Monitor resource for GPU/ CPU-intensive tasks like video processing, model inference, and training using Prometheus , Grafana, alert manager, ELK stack. Collaboration: Work closely with ML engineers to integrate models into production pipelines. Provide tools and frameworks for rapid experimentation and model versioning. Required Skills Basic Python Strong experience with cloud platforms (AWS, GCP, Azure) and cloud-based machine learning services. Expert knowledge of containerization technologies (Docker, Kubernetes) and infrastructure-as-code (Terraform, CloudFormation) Have understanding of Deployment of both synchronous and asynchronous API using Flask, Django, Celery, Redis, RabbitMQ , Kafka Deployed and Scaled AI/ML in Production. Familiarity with deep learning frameworks (TensorFlow, PyTorch). Familiarity with video processing tools like FFMPEG and Dlib for handling dynamic frame data. Basic understanding of ML models Preferred Qualifications Experience in image and video-based deep learning tasks. Familiarity with media streaming and video processing pipelines for real-time generation. Experience with real-time inference and deploying models in latency-sensitive environments. Strong problem-solving skills with a focus on optimising machine learning model infrastructure for scalability and performance.

JOB DESCRIPTION - Why this Job is Amazing: Computer vision engineers apply computer vision and machine learning research to solve real-world problems. Their work uses large sums of data and statistics in order to complete complex tasks and supervised learning as part of computer vision tasks. Their work uses large sums of data and statistics in order to complete complex tasks and supervised learning as part of computer vision tasks. Influences top management internally & externally (industry) to accept new ideas. Creates and conceptualizes solutions to Artivatic in specific discipline. Objective of the position: The purpose of computer vision is to program a computer to understand a scene or features in an image. Typical goals of computer vision include: The detection, segmentation, localization, and recognition of certain objects in images (e.g., human faces) Role and Responsibilities: -Developing novel algorithms and modelling techniques to advance the state of the art in Document and Text Extraction -Image recognition, Object Identification, and Visual Recognition -Working closely with R&D and Machine Learning engineers implementing algorithms that power user and developer-facing products -Be responsible for measuring and optimizing the quality of your algorithms Mandatory traits/ skills: -Excellent skills in developing Python in the Linux environment. -Programming skills with multi-threaded GPUs. -Experience in applying machine learning and computer vision principles to real-world data and working in Scanned and Documented Images -Good knowledge of Computer Science, math, and statistics fundamentals (algorithms and data structures, meshing, sampling theory, linear algebra, etc.) -Knowledge of data science technologies such as Python, Pandas, Scipy, Numpy, matplotlib, etc. -Broad Computer Vision knowledge - Construction, Feature Detection, Segmentation, Classification; Machine/Deep Learning - Algorithm Evaluation, Preparation, Analysis, Modeling, and Execution. -Familiarity with Open CV, Dlib, Yolo, Capsule Network or similar and Open Source AR platforms and products -Have profound knowledge of Seq2Seq, temporal Classification, Opencv, etc. -Should have logical knowledge for generating the real-time dataset. -Added advantage if you have worked in Unstructured Documents -Strong problem-solving and logical skills. -A go-getter kind of attitude with a willingness to learn new technologies -Well-versed in software design paradigms and good development practices Qualifications  Bachelors or Master's degree in Computer Science, Computer vision, or related field with specialization in Image Processing or machine learning.  3-8 Years of Industry experience in Computer Vision  Research experience in Deep Learning models for Image processing or OCR-related field is preferred  Publication record in Deep Learning models for Computer Vision conferences/journals is a plus

Role Summary As an AI Engineer , you will lead the development and deployment of real-time AI modules for facial analysis and vital sign estimation based on video streams. Key Responsibilities Research, prototype, and productionize computer vision models for: Facial expression recognition (emotion classification) Remote photoplethysmography (rPPG) for BPM estimation SpO estimation from RGB video signals Preprocess webcam images for signal enhancement (ROI extraction, denoising) Integrate ML models into the backend (FastAPI-based), processing real-time webcam input Optimize models for latency, accuracy, and resource usage (on CPU/GPU) Deploy AI models as Dockerized microservices (REST/WS-based inference APIs) Work with frontend and backend teams to ensure seamless model integration Conduct internal validation, A/B testing, and ongoing calibration Tech Stack / Tools Languages : Python (must), PyTorch or TensorFlow CV/ML Libraries : OpenCV, Mediapipe, dlib, scikit-learn Signal Processing : numpy/scipy, rPPG libraries (e.g., DeepPhys, MTTS-CAN) Deployment : FastAPI, Docker, ONNX, TorchScript Infra : Redis, PostgreSQL, AWS (GPU EC2, S3, ECS) Required Skills 3+ years of experience building computer vision or bio-signal AI models Hands-on experience with facial emotion recognition using CNNs/RNNs/transformers Familiarity with rPPG-based BPM & SpO estimation from webcam videos Strong background in signal processing , noise reduction, and ROI selection Ability to write production-grade Python code and deploy AI inference services Experience optimizing models for inference (quantization, pruning, ONNX) Nice to Have Experience with real-time WebRTC or webcam processing Familiarity with ML pipelines (MLflow, ClearML, SageMaker) Experience with face tracking (MediaPipe FaceMesh, dlib landmarks) Familiarity with multi-modal emotion detection (face + voice) Knowledge of privacy-preserving AI methods (differential privacy, edge inference) What Youll Own Accurate real-time facial emotion AI module Vital signs (SpO/BPM) module with acceptable medical-grade error margins Robust backend integration for WebSocket/webcam flow Scalable AI deployment strategy for 10K 1M users

Experience: 3+ years Requirements: Excellent knowledge of computer vision concepts, including but not limited to Image Classification, Object Detection, and Semantic Segmentation, developed using state-of-the-art deep learning algorithms. Hands-on experience developing efficient and real-time convolutional neural network (CNN) models for computer vision tasks. Strong proficiency in at least one of the deep learning frameworks, such as PyTorch , TensorFlow , or Caffe, with the ability to apply them to computer vision problems. Quick prototyping skills in Python and coding and debugging proficiency in C++ . Good communication and collaboration skills to work effectively in a team and communicate complex technical concepts. Qualifications: A Ph.D. degree (including candidates at various stages of their Ph.D., such as thesis submission, thesis submitted, degree awaited, synopsis seminar completed, defense completed) in Deep Learning with hands-on coding skills and a passion for an industrial career will be preferred. Master's or Bachelor's degree with thorough industrial work experience in developing computer vision applications using deep learning. Postgraduates or Undergraduates with a strong academic background in Deep Learning, Computer Vision, or related fields, and demonstrated coding skills, are also encouraged to apply. Preferred: Publications in top-tier computer vision conferences like CVPR, ICCV, ECCV , or major AI conferences like NeurIPS. Knowledge of computer vision libraries and tools, including OpenCV and DLib, and a solid understanding of image processing and computer vision fundamentals. Hands-on experience with model compression and pruning techniques in deep learning. Good exposure to various deep learning architectures, such as Artificial Neural Networks (ANN), Deep Neural Networks (DNN) , Convolutional Neural Networks (CNN) , Recurrent Neural Networks (RNN ), and Long Short-Term Memory (LSTM) networks. Familiarity with GPU programming (e.g., CUDA, OpenCL) for efficient deep-learning computations. Pay is competitive as per market standards.

This C/C++ Developer role is responsible and accountable for the quality and coding of a variety of software applications and image processing tools. This includes both hands-on development, trouble shooting, and testing of systems among other technologies. This C/C++ Developer role requires a strong foundation in software development, data structures and image processing as well knowledge in neural network engines for pattern recognition. This role requires to be able to work independently, work in a team environment, and interface with other team resources like people from business or operation. JORDAN BASED. PLEASE SEND YOUR CV TO applicants@keytechsecurity.com Qualifications Required Knowledge/Skills/Abilities: • 7+ years software development experience with C,C++ • Recommended 2+ years software development experience with python is an add-on advantage • Create custom tools for data annotation (C++/Python) • Build C++ Open Source Libraries with cmake • Implement and train Dlib Hog Detector • Implement Fully Connected Neural Network model with Tensorflow C++ • Ability to test python open source deep learning classifiers such as MNIST, SVHN Classifier • Knowledge of Linear Algebra such as matrix and vectors operations • Minimum 4+ Yeas of image processing, machine learning experience using open source/third party neural network engines for OCR • Need to have experience with opensource stacks such as tesseract, Image processing experience with OpenCV, OpenALPR, DLib, TensorFlow. • Experience in Multi-Threading development. • Working knowledge of Object Oriented design, SOLID and design patterns • Experience with Agile development methodology is an add-on advantage • Individual must have experience working the entire product life-cycle and the ability to quickly grasp and distill highly complex user design issues into clean, understandable solutions. • Must be a creative thinker and have a keen interest in ensuring the best possible online experience for clients; possess a fine attention to detail and a disciplined approach to developing applications. • Strong communication skills, oral and written; able to engender trust and respect of team members. • Ability to communicate with and understand the needs of non-technical internal clients • Self-confident, possesses a strong work ethic, and is continually focused on improvement, innovation, and bottom-line results • Highly-motivated self-starter capable of juggling a number of priorities and delivering results on time in a high pressure, dynamic environment • Passionate commitment to the customer and to product quality. Champions the product and the customer's needs and implements a model of continuous improvement in both company goals and project-related tasks

Experience: 4+ years Requirements: Excellent knowledge of computer vision concepts, including but not limited to Image Classification, Object Detection, and Semantic Segmentation, developed using state-of-the-art deep learning algorithms. Hands-on experience developing efficient and real-time convolutional neural network (CNN) models for computer vision tasks. Strong proficiency in at least one of the deep learning frameworks, such as PyTorch, TensorFlow, or Caffe, with the ability to apply them to computer vision problems. Quick prototyping skills in Python and coding and debugging proficiency in C++. Good communication and collaboration skills to work effectively in a team and communicate complex technical concepts. Qualifications: A Ph.D. degree (including candidates at various stages of their Ph.D., such as thesis submission, thesis submitted, degree awaited, synopsis seminar completed, defense completed) in Deep Learning with hands-on coding skills and a passion for an industrial career will be preferred. Master's or Bachelor's degree with thorough industrial work experience in developing computer vision applications using deep learning. Postgraduates or Undergraduates with a strong academic background in Deep Learning, Computer Vision, or related fields, and demonstrated coding skills, are also encouraged to apply. Preferred: Publications in top-tier computer vision conferences like CVPR, ICCV, ECCV, or major AI conferences like NeurIPS. Knowledge of computer vision libraries and tools, including OpenCV and DLib, and a solid understanding of image processing and computer vision fundamentals. Hands-on experience with model compression and pruning techniques in deep learning. Good exposure to various deep learning architectures, such as Artificial Neural Networks (ANN), Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) networks. Familiarity with GPU programming (e.g., CUDA, OpenCL) for efficient deep-learning computations. Pay is competitive as per market standards. Show more Show less

About Our Company: Aerocraft Engineering India PVT Ltd based in Ahmedabad, provides services to US based Architecture, Engineering and Construction group of companies: Russell and Dawson – An Architecture/Engineering/Construction firm (www.rdaep.com) United-BIM – BIM Modeling Services Firm (www.united-bim.com) AORBIS – Procurement as a Service Provider (www.aorbis.com) For AORBIS business, we are looking for experienced Python & AI/ML Developers to design, develop, test, and maintain our Python-based internal web application with a focus on Artificial Intelligence/Machine Learning (AI/ML) technologies. Position: Senior Python & AI/ML Developer Location: Work from Office, Ahmedabad (S G Highway, Makarba) Timings: 12pm to 9pm - Monday to Friday Experience: Minimum 2-6 years Job Location: Ahmedabad (Siddhivinayak Towers, Makarba) Responsibilities: Design and Deploy AI-driven solutions Lead, mentor, and inspire a team of computer vision engineers. Foster a collaborative and innovative work environment. Design and implement computer vision algorithms for geospatial data analysis. Drive the development of Machine Learning Models to automate PDF and construction design analysis. Stay abreast of the latest developments in computer vision, AI, and geospatial technology. Innovate and contribute to the development of new and improved algorithms. Collaborate with Product Managers, Software Engineers, and other stakeholders to integrate AI solutions into our platform. Provide technical leadership and guidance on AI-related projects. Research a combination of primary and secondary research to build an understanding of customer/ internal platform users, their needs, and pain points. Solutioning -developing a hypothesis based on the research, iterating to define product requirements. Designing- working with the design team to translate the product requirements into a delightful UX and UI. Execution -working proactively with engineering teams to build out the product in the most efficient way. Gathering feedback- designing methods to understand how users are using the product, through product analytics, surveys, and conversations. Identifying relevant and impactful feedback and incorporating it in the product roadmap Stakeholder management. Independent long-term thinking -taking a step back from the daily hustle to think about the long-term future of your products. Mentoring - guiding a team of junior APMs and ensuring they are able to grow and take more ownership of product areas. Skills Required: Minimum 5 years of experience in computer vision and handling a team High proficiency in Python / LLM or similar programming language (LLM Mandatory) Applicant should be preferably skilled in image/PDF processing libraries like OpenCV, dLib Open GL, scikit - learn and TensorFlow, PyTorch, Caffe, Keras, Point Cloud Library and Basic Python Libraries (numpy, panda, os). Experience with machine learning especially classification algorithms is required (e.g. k-nn, support vector machine) as well as experience in processing multispectral data Experience with cloud-based (AWS/Azure/GCP) implementation of computer vision solutions. Ability to research and prototype new algorithms. Experience in using Source Control / Project Tracking systems (Github, Jira). Experience in image segmentation, object, and motion detection, tracking, and classification. Benefits: Exposure to US Projects/Design/Standards Company provides Dinner/Snacks/Tea/Coffee Reimbursable Health Insurance 15 paid leave annually & 10 Public Holidays Show more Show less