AI/ML Engineer - GTRI-ICL

at  Georgia Tech Research Institute

OVERVIEW:

The Georgia Tech Research Institute (GTRI) is the nonprofit, applied research division of the Georgia Institute of Technology (Georgia Tech). Founded in 1934 as the Engineering Experiment Station, GTRI has grown to more than 2,900 employees, supporting eight laboratories in over 20 locations around the country and performing more than $940 million of problem-solving research annually for government and industry. GTRI’s renowned researchers combine science, engineering, economics, policy, and technical expertise to solve complex problems for the U.S. federal government, state, and industry.

PROJECT/UNIT DESCRIPTION

The Advanced Computing and Artificial Intelligence Division (ACAID) within the ICL Lab is seeking a Mid to Senior Artificial Intelligence Scientist to join our team of passionate researchers. We seek an experienced Scientist who can support our research efforts by matching cutting-edge algorithms with advanced computing technologies to realize solutions for the Nation’s most challenging problems. The ideal candidate will have broad and deep expertise in the application of analytic tools and machine learning techniques. A strong candidate will have interest and practical experience in AI applications for a wind range of research domains to include DoD, DOE and Healthcare industry.
This position will focus on the design, development and deployment of AI pipeline designs. The candidate will work closely with staff members in a collaborative working environment. This is an excellent opportunity for a motivated, results-oriented professional. We are seeking people who get excited about working with data, developing evidence base data driven solutions.
The ACAID Division works with a diverse group of organizations and agencies in National Security and the public health space. The ideal candidate must be able to communicate complex technical material clearly to a wide variety of audiences including academia, conference proceedings, management, business development leads, prospective and existing customers.

REQUIRED MINIMUM QUALIFICATIONS

• Strong understanding of AI development in cloud enviroments 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

TRAVEL REQUIREMENTS

10% - 25% travel

EDUCATION AND LENGTH OF EXPERIENCE

This position vacancy is an open-rank announcement. The final job offer will be dependent on candidate qualifications in alignment with Research Faculty Extension Professional ranks as outlined in section 3.2.1 of the Georgia Tech Faculty Handbook

• 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
• 0 years of related experience with a Masters’ 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

U.S. CITIZENSHIP REQUIREMENTS

Due to our research contracts with the U.S. federal government, candidates for this position must be U.S. Citizens.

JOB PURPOSE

The Artificial Intelligence/Machine Learning (AI/ML) Engineer develops AI/ML algorithms, cloud computing, and/or heterogeneous distributed computing infrastructures to support the deployment of AI/ML applications. The AI/ML Engineer also researches the mathematical foundations and frameworks for nonlinear systems characterized by time-varying and emerging dynamics of evolving or adaptive systems. The AI/ML Engineer develops technical solutions at the leading edge of Artificial Intelligence, Machine Learning, Genetic Programming, Computer Vision, and advanced data processing, filtering, and fusion techniques in high-performance computing and distributed heterogeneous computing environments. The AI/ML Engineer writes parallel processing programs to deploy ML models developed by data scientists into more complex systems. The AI/ML Engineer has familiarity with state-of-the-art, open-source software frameworks and high-performance computing accelerators for machine learning. When conducting research, the AI/ML Engineer leverages the most recent advances in statistical analysis of large data sets to advance state-of-the-art automated sensor and data processing for a broad range of intelligent and sensor-enabled systems.

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