Why This Role Stands Out
This hybrid Applications Developer role at Level Up, LLC offers exciting opportunities to build cutting-edge solutions within the Intelligence Community, fostering significant career growth and skill development in areas like Java Spring, AWS, and text analytics. You'll thrive here if you are a proactive developer eager to collaborate and contribute to impactful projects, so don't miss the chance to apply!
Quick Overview
Job Description
This role will support applications development for a variety of tools and initiatives focused on streamlining operations, automating processes, and aligning customer solutions to the overarching digital architecture. The ideal candidate will help promote state-of-the-art IT solutions, collaborating with IT mission partners to share technology and lessons learned and ensure records management processes and requirements are included in the early design stages of IT solutions across the Intelligence Community. Additionally, this individual will work in concert with the customer technical interfaces to ensure future plans for technology are in line with the plans for the overall customer architecture. Demonstrated experience with:
- Building web applications in the Java Spring framework
- Working in Linux (Bash) shell scripting
- Development of applications in the Amazon Web Services cloud environment
- Extract, transform, and load (ETL) on large raw data sets
- Developing web-based platforms to perform searches or analytics on large data sets
- Design, develop, test and implement new applications based on project requirements
Desired Skills
Demonstrated experience with:
- Deployment of applications in the Amazon Web Services cloud environment
- Solr or ElasticSearch
- Proficiency in Python software development, especially web service development in Flask or Django
- Building web applications using the Angular 2+ framework
- Text analytics and its applications/role/use in business intelligence/business analytics (i.e. search, entity extraction, sentiment analysis, document summarization, document categorization)
- Researching and implementing machine learning algorithms for use in production systems
- Developing proof of concepts of new technologies and evaluating the state of the art in machine
- learning algorithms for text analytics
- Machine learning frameworks such as PyTorch, Keras, Tensorflow
- Data visualization tools (i.e. Tableau, Pandas, D3 s, ggplot, etc)
- In memory datastores (i.e. ElasticCache, Redis)
- NoSQL data stores such as MongoDB or DynamoDB
- MySQL or Postgres
- Natural Language Processing tools such as spaCy, NLTK, Stanford CoreNLP, or Gensim
- Natural Language Processing
- Optical character recognition (OCR) or image detection
- Developing solutions using opensource PDF libraries (Java, Python, or Javascript)
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