6 Faster Rcnn Jobs

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.,

You will be responsible for solving complex data problems using deep learning techniques in computer vision OR Natural Language processing. Your primary tasks will include delivering production-ready models, meeting project requirements and timelines, identifying success metrics, and monitoring them to ensure high-quality output for the client. Additionally, you will be expected to share ideas and learnings with the team. To succeed in this role, you must have at least 2+ years of working experience with Python programming. Applied experience with Deep Learning algorithms such as Convolutional Neural Networks, Recurrent Neural Networks, and machine learning expertise with exposure to frameworks like Tensorflow, Keras, pytorch, Caffe, MXNet is mandatory. You should also possess a minimum of 2 years of experience in the NLP/Computer vision domain. Exposure to DL Model optimization, transfer learning techniques, and SOTA algorithms in computer vision &/or Natural language processing will be beneficial for tasks like Object detection, tracking, classification, text summarization, etc. Strong verbal and written communication skills for effective interactions with the team and clients are essential. In this role, you will enjoy a fun workplace environment with a flat job hierarchy, flexible work hours, casual dress code, and a disciplined workplace environment. Additionally, you will have opportunities for learning & development, team cohesion, task autonomy, smooth reporting, and extensive training. The company's HR policies include the POSH Act for inclusivity, a flexible leave policy, monthly paid leaves, and bonus & incentives. You will also be motivated through team appreciation, individual awards, performance rewards, and salary appraisals.,

You are an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. Leveraging deep technical expertise, Agile methodologies, and data-driven intelligence, you modernize systems of engagement and simplify human/tech interaction. Amazing things happen in environments where everyone feels a true sense of belonging and has the skills and opportunities to succeed. Investing in talent and supporting career growth is a priority, always looking for amazing talent to contribute to growth by delivering top results for clients. Join the team to challenge yourself and accomplish meaningful work. As a highly experienced Computer Vision Architect with deep expertise in Python, you will design and lead the development of cutting-edge vision-based systems. Architecting scalable solutions leveraging advanced image and video processing, deep learning, and real-time inference, you will collaborate with cross-functional teams to deliver high-performance, production-grade computer vision platforms. Key Responsibilities: - Architect and design end-to-end computer vision solutions for real-world applications like object detection, tracking, OCR, facial recognition, and scene understanding. - Lead R&D initiatives and prototype development using modern CV frameworks such as OpenCV, PyTorch, TensorFlow. - Optimize computer vision models for performance, scalability, and deployment on cloud, edge, or embedded systems. - Define architecture standards and best practices for Python-based CV pipelines. - Collaborate with product teams, data scientists, and ML engineers to translate business requirements into technical solutions. - Stay updated with the latest advancements in computer vision, deep learning, and AI. - Mentor junior developers and contribute to code reviews, design discussions, and technical documentation. Required Skills & Qualifications: - Bachelors or Masters degree in Computer Science, Electrical Engineering, or related field (PhD is a plus). - 8+ years of software development experience, with 5+ years in computer vision and deep learning. - Proficiency in Python and libraries such as OpenCV, NumPy, scikit-image, Pillow. - Experience with deep learning frameworks like PyTorch, TensorFlow, or Keras. - Strong understanding of CNNs, object detection (YOLO, SSD, Faster R-CNN), semantic segmentation, and image classification. - Knowledge of MLOps, model deployment strategies (e.g., ONNX, TensorRT), and containerization (Docker/Kubernetes). - Experience working with video analytics, image annotation tools, and large-scale dataset pipelines. - Familiarity with edge deployment (Jetson, Raspberry Pi, etc.) or cloud AI services (AWS SageMaker, Azure ML, GCP AI).,

As a Lead Data Scientist/AI Product Owner at a reputed IT MNC in Gurgaon, your primary responsibility will be AI Model Development & Deployment, focusing on Computer Vision & Deep Learning. You will be leading the design and implementation of computer vision models for various tasks such as object detection, tracking, segmentation, and action recognition. Your expertise will include architectures like YOLO (v4, v5, v8), Vision Transformers, Mask R-CNN, Faster R-CNN, LSTMs, and Spatio-Temporal Models for image and video analysis. Additionally, you will contextualize the model for challenging situations such as poor detection through specific training on different scenarios. Another key aspect of your role will involve Reinforcement Learning & Model Explainability, where you will develop and integrate reinforcement learning models to optimize decision-making in dynamic AI environments. You will work with techniques such as Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), A3C, SAC, and other RL methods. Furthermore, you will lead the development of a Scalable Data Model for AI Model Training Pipelines, overseeing the end-to-end data preparation process, including data gathering, annotation, and quality review before training. You will focus on enhancing the quality and volume of training data to continually improve model performance and have the ability to think through the data model for future enhancements. In terms of technical skills, you are expected to have a proven track record of leading and delivering AI products, hands-on expertise with advanced AI models, experience in managing and mentoring a small team of data scientists, proficiency 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. Nice-to-have skills include Experimentation, Iterative Improvement and Testing, Collaboration with Engineering and Product Teams, and Team Leadership. To qualify for this role, you should have at least 10 years of hands-on experience in AI with a solid background in object detection, image and video processing, and computer vision.,

As a Senior AI Engineer at Avathon, you will be part of a cutting-edge team revolutionizing industrial AI by developing groundbreaking solutions that shape the future. Your role will involve designing, training, and deploying computer vision models using frameworks like TensorFlow, PyTorch, or ONNX to harness the full potential of operational data. You will utilize your expertise in model optimization techniques such as quantization, pruning, distillation, and structured sparsity to enhance performance on edge devices and low-power hardware. Hands-on experience with state-of-the-art architectures like YOLO, Faster R-CNN, and Vision Transformers will be essential for optimizing models for deployment in industrial environments. Your strong understanding of image preprocessing, feature extraction, traditional computer vision techniques, and end-to-end model pipelines will enable you to create real-time virtual replicas of physical assets for predictive maintenance, performance simulation, and operational optimization. Proficiency in Python and C++ for developing AI solutions, along with experience in parallel processing and hardware-aware optimizations, will be key in driving AI-driven projects that have a meaningful impact across industries. Furthermore, your expertise in profiling and optimizing model inference speed, memory usage, and throughput for resource-constrained environments, as well as practical experience in deploying AI models on embedded systems and low-power hardware, will be crucial for anomaly detection, performance forecasting, and asset lifetime extension in industrial settings. Familiarity with MLOps practices, version control with Git, and collaborative workflows will ensure efficient management of AI workflows and seamless collaboration within cross-functional teams. Join Avathon in Bengaluru and thrive in a high-growth environment where agility, collaboration, and rapid professional growth are the norm. Make a difference by working on AI-driven projects that drive real change across industries and improve lives. If you are a forward-thinking AI Engineer with a passion for innovation and a drive to create scalable solutions in industrial AI, we invite you to be a part of our team and contribute to the revolutionizing of industrial AI.,

Ability to multitask and work on multiple engagements related to different domains Work in a highly collaborative and fast paced environment by interacting with the stakeholders and various IT teams within the company to facilitate the design and development of ML/AI solutions Responsible for the successful delivery of all allocated projects with respect to schedule, quality, and customer satisfaction Work with the pre-sales team on RFP, RFIs and help them solutioning for different AI/ML use cases Evaluate latest technologies, decide technical feasibility, and drive solution implementations Follow Agile standards and methodologies in all phases of the project and ensure excellence in delivery to customers Refine coding standards, software development guidelines, and best practices within the organization, and ensure adherence to those Mentor other associate architects, engineers and young talent within the organization, define and track their growth parameters. Must have skills: Strong interpersonal and written skills with clear and precise communication. Experience working in an Agile and competitive environment. Technical leadership experience handling large teams. Stakeholder interaction experience both within the organization and outside with clients. Strong analytical and quantitative skill set with proven experience solving business problems across domains. Very good with EDA, Hypothesis Testing, Feature Engineering. Hands-on with Python/R programming and ML/Viz. libraries/frameworks like Scikit-Learn, Pandas, Matplotlib, Seaborn, D3.js, Tensorflow, Pytorch, Keras. Experience with ML algorithms such as Regression and Classification (Decision-trees, Random Forests, SVM, ANNs), Clustering (k-means, DBSCAN), Dimension Reduction (PCA, SVD), Ensemble techniques (XGBoost, CatBoost, LightGBM). Basic image enhancement techniques such contrast enhancement, blurring, histogram equalization, etc using OpenCV. Experience with DL/CV techniques like CNNs, Faster RCNN, Mask RCNN, YOLO, SSD, Detectron2 for various use cases related to image such as Image Classification, Object Detection, Image Segmentation, etc. Traditional NLP - Bag of words, tf-idf, Stemming, Lemmatization, Tokenization, POS tagging, Coreference Resolution, Dependency and Constituency Parsing, Named Entity Recognition. NLP: NLU vs NLG, Vector Space modeling and text representation techniques in NLP, Knowledge/experience using RNNs, LSTMS, Sequence modeling and Attention mechanism, Transformers, BERT, GPT and their SOTA variants, Sequence modeling, Attention modeling, BERT, Transformers.Using the above-mentioned techniques for Text classification, Sentiment Analysis, Semantic similarity, Entity Extraction, Document summarization, NLI, Question-Answering, Machine Translation, etc. Forecasting modeling experience both on univariate and multivariate data using algorithms like Linear Regression, Neural Networks, Exponential Smoothing, Holt s Winters, ARIMA, SARIMA, LSTM. Identify appropriate objective functions, regularization techniques, performance metrics based on the use case and should be able to perform cross-validation, hyperparameter tuning, and error analysis. Experience/Knowledge working on Intelligent Document processing solutions using open-source technologies like OCR using Tesseract, text-block, ROI detection using OpenCV, etc. Experience/Knowledge working on solutions using Cloud based Document processing products like Google Document AI, Amazon Textract, Microsoft Azure Form Recognizer, etc. Proven experience building and deploying AI/ML solutions in production using open source or cloud tools such as MLflow, Kubeflow, TFX, Feature Store, etc. Hands-on AI/ML experience with any one cloud platform (GCP, Azure, AWS) either using the modeling options (Vertex AI, SageMaker, Azure ML) or leveraging the APIs (Textract,Vision, Text Extraction, Speech-to-text, Text-to-speech, Translation etc.). Nice to have skills: Any pre-sales experience Hands-on experience with any visualization tool like Tableau, Power BI, Looker Studio Build APIs using frameworks such as Flask, Django, FastAPI Distributed training for deep learning using frameworks like PyTorch, TensorFlow Advanced image processing using OpenCV, Feature Detection and Matching using SIRF/SURF/FAST/BRIEF Advanced recommender systems using model based techniques like KNN, Matrix Factorization, SVD, etc and and/or Deep Learning methods Docker containerization of microservices, deployment on cloud compute resources and orchestration using popular frameworks like Kubernetes Experience with either or all of Knowledge Graphs, Federated Learning, Deep Reinforcement Learning Cloud Certification - Machine Learning and/or Cloud Architect