3.0 - 7.0 years

0 Lacs

karnataka

On-site

As an AI/ML Developer, you will be responsible for utilizing programming languages such as Python for AI/ML development. Your proficiency in libraries like NumPy, Pandas for data manipulation, Matplotlib, Seaborn, Plotly for data visualization, and Scikit-learn for classical ML algorithms will be crucial. Familiarity with R, Java, or C++ is a plus, especially for performance-critical applications. Your role will involve building models using Machine Learning & Deep Learning Frameworks such as TensorFlow and Keras for deep learning, PyTorch for research-grade and production-ready models, and XGBoost, LightGBM, or CatBoost for gradient boosting. Understanding model training, validation, hyperparameter tuning, and evaluation metrics like ROC-AUC, F1-score, precision/recall will be essential. In the field of Natural Language Processing (NLP), you will work with text preprocessing techniques like tokenization, stemming, lemmatization, vectorization techniques such as TF-IDF, Word2Vec, GloVe, and Transformer-based models like BERT, GPT, T5 using Hugging Face Transformers. Experience with text classification, named entity recognition (NER), question answering, or chatbot development will be required. For Computer Vision (CV), your experience with image classification, object detection, segmentation, and libraries like OpenCV, Pillow, and Albumentations will be utilized. Proficiency in pretrained models (e.g., ResNet, YOLO, EfficientNet) and transfer learning is expected. You will also handle Data Engineering & Pipelines by building and managing data ingestion and preprocessing pipelines using tools like Apache Airflow, Luigi, Pandas, Dask. Experience with structured (CSV, SQL) and unstructured (text, images, audio) data will be beneficial. Furthermore, your role will involve Model Deployment & MLOps where you will deploy models as REST APIs using Flask, FastAPI, or Django, batch jobs, or real-time inference services. Familiarity with Docker for containerization, Kubernetes for orchestration, and MLflow, Kubeflow, or SageMaker for model tracking and lifecycle management will be necessary. In addition, your hands-on experience with at least one cloud provider such as AWS (S3, EC2, SageMaker, Lambda), Google Cloud (Vertex AI, BigQuery, Cloud Functions), or Azure (Machine Learning Studio, Blob Storage) will be required. Understanding cloud storage, compute services, and cost optimization is essential. Your proficiency in SQL for querying relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and familiarity with big data tools like Apache Spark, Hadoop, or Databricks will be valuable. Experience with Git and platforms like GitHub, GitLab, or Bitbucket will be essential for Version Control & Collaboration. Familiarity with Agile/Scrum methodologies and tools like JIRA, Trello, or Asana will also be beneficial. Moreover, you will be responsible for writing unit tests and integration tests for ML code and using tools like pytest, unittest, and debuggers to ensure the quality of the code. This position is Full-time and Permanent with benefits including Provident Fund and Work from home option. The work location is in person.,

Posted 4 days ago

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Computer Vision Intern FieldAssist

0.0 - 4.0 years

0 Lacs

haryana

On-site

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.,

Posted 1 month ago

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