Java J2Ee Backend Software Engineer Data Science Practitioner Full Time

Sumpraxis Services Pvt Ltd

5-6yrs

51 days ago

Delhi NCR

Primary Skills : python, github, stanford corenlp, maven, nltk, neural networks, numpy, machine learning, javascript, artificial intelligence, spring boot, spacy, tensorflow.

Secondary Skills : java, nlp, data science, design patterns, matplotlib, j2ee, jenkins, software engineering, aws, textblob.

No. of Positions : 1

Salary Range : 14-18 lac

Job Description

Technical Skills and Background

  • Min 5+ years of professional artificial intelligence development experience.
  • Experienced and proficient into artificial intelligence components - NLP and ML and Neural Network etc.
  • Experienced into implementation of NLP by using libraries like - NLTK, Spacy, TextBlob, Stanford corenlp etc.
  • Experienced into implementation of ML (Supervised and Un-Supervised and Reinforcement Machine Learning) by using libraries like - Scikit-Learn, TensorFlow etc.
  • Experience must be in implementing ML algorithm like Linear & Logistic Regression, SVM, Random Forest, NVC, K-means, vectorization etc.
  • Experienced with python data analysis like pandas, numpy, matplotlib etc.
  • Expertise into AI and python programming language.
  • Expertise into text parsing using python or java.
  • Expertise into writing the NLP and ML independently without external api support like GoogleML etc.
  • Experienced and proficient in designing, writing, testing and deploying software solutions in Python, Java J2EE, Spring Boot, and other related software libraries and tools.
  • Experienced with other programming languages including Python and JavaScript.
  • Experience with common development lifecycle tools such as Jira, GitHub, Maven, Jenkins and others.
  • Bachelor's and/or Master's degree in Computer Science, Computer Engineering or related technical discipline.
  • Experience in developing distributed/scalable systems and high-volume data driven applications.
  • Experience with Micro-Services architecture and other common design patterns.
  • Experience with AWS or other leading cloud platforms and services.
  • Knowledge of professional software engineering and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Hands-on experience with building and operating large scale machine learning systems, algorithms and best practices.
  • Familiar with large scale data systems and variety of database platforms including common opensource relational databases, no-sql databases and graph databases.

 

Job Description

Technical Skills and Background

  • Min 5+ years of professional artificial intelligence development experience.
  • Experienced and proficient into artificial intelligence components - NLP and ML and Neural Network etc.
  • Experienced into implementation of NLP by using libraries like - NLTK, Spacy, TextBlob, Stanford corenlp etc.
  • Experienced into implementation of ML (Supervised and Un-Supervised and Reinforcement Machine Learning) by using libraries like - Scikit-Learn, TensorFlow etc.
  • Experience must be in implementing ML algorithm like Linear & Logistic Regression, SVM, Random Forest, NVC, K-means, vectorization etc.
  • Experienced with python data analysis like pandas, numpy, matplotlib etc.
  • Expertise into AI and python programming language.
  • Expertise into text parsing using python or java.
  • Expertise into writing the NLP and ML independently without external api support like GoogleML etc.
  • Experienced and proficient in designing, writing, testing and deploying software solutions in Python, Java J2EE, Spring Boot, and other related software libraries and tools.
  • Experienced with other programming languages including Python and JavaScript.
  • Experience with common development lifecycle tools such as Jira, GitHub, Maven, Jenkins and others.
  • Bachelor's and/or Master's degree in Computer Science, Computer Engineering or related technical discipline.
  • Experience in developing distributed/scalable systems and high-volume data driven applications.
  • Experience with Micro-Services architecture and other common design patterns.
  • Experience with AWS or other leading cloud platforms and services.
  • Knowledge of professional software engineering and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Hands-on experience with building and operating large scale machine learning systems, algorithms and best practices.
  • Familiar with large scale data systems and variety of database platforms including common opensource relational databases, no-sql databases and graph databases.

 

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