Press Enter

PROJECT TITLE

    Press Enter

    NOTIFICATIONS

    receipt
    Data Scientist at Esri (New Delhi, India)
    Esri Employer
    New Delhi, India
    Job Type
    Job Location
    Full Time
    New Delhi, India

    Job Description:

    OVERVIEW



    Are you passionate about applying AI and machine learning to solve some of the world’s biggest challenges? So are we! Esri is the world leader in geographic information systems (GIS) and developer of ArcGIS, the leading mapping and analytics software used in 75 percent of Fortune 500 companies. At the Esri R&D Center-New Delhi, we are applying cutting-edge deep learning techniques to revolutionize geospatial analysis and derive insight from imagery and location data.
     
    Join our team of exceptional data scientists and software engineers to deliver a spatial data science platform, develop industry-leading AI models for satellite imagery, and build world-class Geo AI solutions.



    RESPONSIBILITIES



    • Develop and train deep learning models for computer vision problems such as object detection, image classification, road detection, building footprint segmentation, and 3D point cloud segmentation

    • Develop processes and tools to monitor model performance and accuracy

    • Integrate ArcGIS with popular machine learning and deep learning libraries such as Scikit-learn, Tensorflow/Keras, and PyTorch/FastAI

    • Design, test, release, and support AI capabilities in the ArcGIS platform to enhance overall product quality and applicability for supporting data science and deep learning workflows

    • Author and maintain geospatial data science samples using ArcGIS and machine learning/deep learning libraries like Tensorflow and PyTorch


    REQUIREMENTS





    • 3+ years of experience with Python

    • 3+ years of practical machine learning experience, some of which is within established technical organizations

    • Self-learner with coursework in and extensive knowledge of machine learning and deep learning

    • Experience with Python machine learning and deep learning libraries such as Scikit-learn, Pandas, PyTorch/FastAI, or TensorFlow/Keras

    • Understanding of machine learning as well as deep learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Random Forests, CNNs, RNNs, LSTMs

    • Ability to design and implement deep learning models for object detection, semantic and instance segmentation, GANs

    • Experience in data visualization in Jupyter Notebooks using matplotlib and other libraries

    • Experience with Hyperparameter-tuning and training models to a high level of accuracy

    • Ability to perform data extraction, transformation, loading from multiple data sources and sinks

    • Bachelor's or master's in computer science, engineering, or related disciplines from IITs or other top tier engineering colleges




    RECOMMENDED QUALIFICATIONS



    • Experience applying deep learning to satellite or medical imagery

    • Familiarity with ArcGIS suite of products and concepts of GIS, including working with ArcGIS API for Python

    • Knowledge of deep learning for natural language processing, probabilistic programming, and reinforcement learning

    • Experience with CUDA/GPU programming

    • Experience with distributed training of deep learning models and big data machine learning using Spark ML

    • Familiarity with one or more of the following: Hadoop HDFS, Spark, Accumulo, Presto, MongoDB, Elastic Search, Cassandra, HBase, R, Mahout, Pig, Hive, DC/OS, Kubernetes

    • Master's or PhD in mathematics, statistics, computer science, or related field, depending on position level

    Benefits:

    Certificate
    Flexible Hours
    Letter of Recommendation
    Note : This project is an external project, and it was posted on the platform by the Gradbee Team. We curate all the internships available across the internet by visiting company websites, and social networks like Facebook, LinkedIn, WhatsApp, Twitter etc. If you are the owner of this internship / project and need to get it removed, kindly mail us at [email protected]