2 Mask Rcnn Jobs

As a Machine Learning Engineer specializing in Computer Vision, you will play a crucial role in designing, developing, and deploying cutting-edge computer vision models and algorithms for real-world robotic applications. Working alongside a talented team, you will utilize state-of-the-art deep learning techniques to solve complex vision problems ranging from object detection to image segmentation and 3D perception. Your contributions will directly influence the evolution of intelligent systems within the field of robotics. This position is based on-site in Pune and requires immediate availability for joining within one month. Qualifications: - Educational Background: B.Tech., B.S., or B.E. in CSE, EE, ECE, ME, Data Science, AI, or related fields with a minimum of 2 years of hands-on experience in Computer Vision and Machine Learning. Alternatively, an M.S. or M.Tech. in the same disciplines with 2 years of practical experience in Computer Vision and Python programming. - Technical Expertise: You should possess strong experience in developing deep learning models and algorithms for various computer vision tasks, including object detection, image classification, segmentation, and keypoint detection. Proficiency in Python and ML frameworks like PyTorch, TensorFlow, or Keras is essential. Additionally, experience with OpenCV for image processing and computer vision pipelines is required. A solid understanding of convolutional neural networks (CNNs) and other vision-specific architectures such as YOLO, Mask R-CNN, and EfficientNet is expected. Ability to build, test, and deploy robust models using PyTest or PyUnit testing frameworks is necessary. Hands-on experience with data augmentation, transformation, and preprocessing techniques for visual data is also a key requirement. Familiarity with version control using Git is a plus. - Desirable Skills: Experience with 3D vision, stereo vision, or depth sensing technologies will be advantageous. Familiarity with ROS2 for integrating vision systems into robotic platforms, understanding of sensor fusion techniques (e.g., LiDAR, depth cameras, IMUs), exposure to MLOps for deploying and maintaining computer vision models in production environments, knowledge of CMake for building and integrating machine learning and vision-based solutions, experience with cloud-based solutions for computer vision, and ability to work with CUDA, GPU-accelerated libraries, and distributed computing environments are desirable skills. Location: This role is on-site in Pune, India, and immediate availability for joining is required. Why Join Us - Shape the future of robotics and AI by focusing on state-of-the-art computer vision applications. - Work in a dynamic and collaborative environment with a team of highly motivated engineers. - Competitive salary and benefits package, including performance-based incentives. - Opportunities for growth and professional development, including mentorship from industry experts. If you are passionate about leveraging deep learning and computer vision to develop intelligent systems that perceive and interact with the world, we look forward to hearing from you!,

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