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    AI/ML Software Engineer - Atlanta, United States - Insight Global

    Insight Global
    Insight Global Atlanta, United States

    1 day ago

    Insight Global background
    Description

    Required Minimum Qualifications

    • 2 years of related experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Technology, High Performance Computing, Analytics, Artificial Intelligence, Electrical Engineering, Aerospace Engineering, Civil Engineering or related AI research focused field
    • Strong understanding of AI development in cloud environments such as AWS, Azure, Google Cloud/Colaboratory
    • Experience with Scala, Spark, SQL, MATLAB, GitHub, Probability & Statistic and Machine Learning
    • Passion for working with data (can think in data structures)
    • Ability to work well with a variety of teams with diverse skill sets

    Preferred Qualifications

    • Advanced degree in Data Science, Computer Science, Electrical Engineering, Aerospace Engineering, Civil Engineering or related AI field
    • Documented experience conducting advanced research in AI pipeline design using proven Data Science methodologies as well as System Engineering practices.
    • Fundamental programming skills in core data science languages such as Python, R, MATLAB and SQL
    • Experience modeling data in JSON, XML and Entity Relational Diagraming (ERD) design
    • Experience working with cloud-based analytics environment, such as Databricks, Azure ML and AWS
    • Conceptual development in RStudio, JupyterLab and/or Jupyter Notebooks
    • Experience working with databases (I.e. configuring, deploying, securing and maintaining)
    • Experience working with government systems
    • Experience writing research proposals and documenting results
    • Currently possess or can obtain a DoD security clearance up to TS/SCI

    Key Responsibilities

    • Apply tools and frameworks to deploy machine learning models
    • Conduct data conditioning, processing, filtering, and fusion to support the creation of automated algorithms
    • Make decisions regarding implementation based on available hardware (e.g., embedded systems, cloud, server infrastructure)
    • Design application logging capabilities and perform debugging with available logs

    Additional Responsibilities

    • Applying the Cross Industry Standard Process for Data Mining (CRIPS-DM)
    • Data parsing, preparation and fusing of disparate data sources using fundamental data python libraries and established practices and procedures
    • Independently conducting exploratory data analysis, documenting and presenting findings to senior leadership and decision makers
    • Applying data collection techniques in support of ETL and ELT
    • Database modeling, data design and application of stored procedures, stored functions and triggers
    • Application of Machine Learning techniques such as supervised, unsupervised and semi-supervised learning
    • Application of Natural Language Processing techniques
    • Present research at conferences, contribute to business development, and meet with customers
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