NLP Developer
Prodapt
Date: 3 days ago
City: Bengaluru, Karnataka
Contract type: Full time

Overview
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Responsibilities
An NLP Engineer focuses on designing and implementing algorithms and models that enable machines to understand, interpret, and respond to human language. The role combines expertise in linguistics, machine learning, and software development to build applications that process and analyze large amounts of natural language data.
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Requirements
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Additional Skills:
Kubernetes: Strong experience in deploying and scaling applications, managing secrets, and troubleshooting within Kubernetes environments. K8s networking, CNI, VLAN and CNS
Google Cloud: Familiarity with Google Cloud Build, Cloud Deploy,Cloud Functions, Secret Manager, GCS-storage
Virtualization & Containerization: Understanding of virtualization concepts and experience with containerization technologies, including KubeVirt. Proficient in building and deploying containers
CI/CD, DevOps: Experienced in automating build processes, module testing, static code analysis, integration testing, application packaging, vulnerability scanning, and release management.
Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Responsibilities
An NLP Engineer focuses on designing and implementing algorithms and models that enable machines to understand, interpret, and respond to human language. The role combines expertise in linguistics, machine learning, and software development to build applications that process and analyze large amounts of natural language data.
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Requirements
Must Have Skills
Scripting/Programming: Skilled in Shell and Python/ Java for automation and tool development. Familiarity with NLP libraries like NLTK or spaCy or Tensor flow
Data Analysis: Strong analytical skills to clean, preprocess, and analyze large datasets
Good understanding of Machine Learning & Deep Learning
Additional Skills:
Kubernetes: Strong experience in deploying and scaling applications, managing secrets, and troubleshooting within Kubernetes environments. K8s networking, CNI, VLAN and CNS
Google Cloud: Familiarity with Google Cloud Build, Cloud Deploy,Cloud Functions, Secret Manager, GCS-storage
Virtualization & Containerization: Understanding of virtualization concepts and experience with containerization technologies, including KubeVirt. Proficient in building and deploying containers
CI/CD, DevOps: Experienced in automating build processes, module testing, static code analysis, integration testing, application packaging, vulnerability scanning, and release management.
Configuration Management: Proficient with tools such as Terraform and Ansible for infrastructure as code.
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