AI/ML Engineer - SME

• Location: McLean, Virginia
• Type: Contract
• Job #3258

Title: AI/ML Engineer - SME

• Supporting DO/ODDO
  • Mclean & Chantilly
  • Tech Stack: (e.g., MongoDB, Elastic search, Docker and NodeJS
• *Clearance: *Active TS/SCI w/ Polygraph needed to apply *
  Company Overview:
  Cornerstone Defense is the Employer of Choice within the Intelligence, Defense, and Space communities of the U.S. Government. Realizing early on that our most prized assets are our employees, we continually focus our attention on improving the overall work/life experience they have supporting the mission. Our Team is pushed every day to use their industry leading knowledge to provide end-to-end solutions to combat our nation's toughest and most secure problems. If you are looking for a place to not only be professionally challenged, but encouraged and supported by a company that cares, don't look any further than Cornerstone Defense.

JOB DESCRIPTION
The AI/ML Engineer will develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning and use the right combination of tools and frameworks to turn a set of data points into objective answers to help senior leadership make informed decisions. The Data Scientist will apply data mining techniques perform statistical analysis, and build high-quality prediction models. The Data Scientist's ability to obtain data through advanced computerized models and extrapolation of data patterns through advanced algorithms to explain how the information will influence the specific project will be an essential function to providing customers a better comprehension of the data.
The AI/ML Engineer will work closely with customer management, other project managers, system architects, data scientists, data engineers, and machine learning engineers to formulate recommendations for enhancements and improvements geared towards utilizing innovative engineering solutions.

REQUIRED KNOWLEDGE/SKILLS

BS/BA in Software Engineering, Science, Mathematics, or similar OR equivalent combination of education and experience

Familiarization with Large Language Model (LLM) architectures and training procedures

Experience with search architecture tools (ex - Solr, ElasticSearch)

Big Data Frameworks such as Spark or Hadoop

Data Science frameworks such as Keras, Tensorflow, or Theano

Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL

Experience with GPU processing

Experience with word2vec or doc2vec algorithms

Proficient in Java and Python

Must know to use an IDE to code (ex - Visual Studio Code, IntelliJ, Eclipse, NetBeans)

Experience with interacting in a Linux environment (ex - Bash scripting, VI)

Intrapersonal communication skills

Ability to work well in a constantly evolving work environment
DESIRED KNOWLEDGE/SKILLS

Familiarity with Source code management and integration (ex - GitHub/GitLab, Jenkins)

Hands on experience with cloud technology (AWS / C2S)

Experience in an Agile environment

Experience with testing frameworks (ex - Junit, Mockito, Swagger, Postman)

Experience with relational databases (ex - Oracle / MySql)

Experience with JavaScript / Typescript

Experience with front end development (ex - Angular 2+, React, HTML, CSS, JQuery)
KEY RESPONSIBILITES

Develop and train Large Language Models (LLMs) in support of the customer mission

Investigate business area processes for creative implementation of LLMs

Apply data mining techniques to perform statistical analysis

Assists with technical planning activities, including roadmap development and systems integration.

Collaborates with a variety of customers and contractors on a regular basis, which may include technical consultation, meeting coordination and support (e.g., TEMs), and preparation/support of technical briefings.

Participates in the development of technical project plans, reports, and contract (e.g., PMR) briefings.
The ideal candidate will work closely with data scientists, analysts, and customer stakeholders to create and deploy new product features. The AI/ML Engineer will establish scalable, efficient, automated processes for data analyses, model development, validation and implementation.