Software Engineer, Applied AI

State Affairs•Washington, DC

17h•Onsite

About The Position

State Affairs is the nation’s leading news and policy intelligence platform focused on state governments. We combine nonpartisan coverage of Statehouses across the country alongside state government data and AI-native tools into a singular platform. We inform and empower decision makers, policy professionals and citizens through our award-winning journalism and data – delivering profound insights to help our customers decode and act on state politics and policy. We’re building a category-defining business that will reshape America as we strengthen visibility into what’s happening and why at the state level. We are hiring a Software Engineer, Applied AI to join our team located in Washington, DC.

Requirements

Master’s degree or PhD in computer science, engineering, or related field
Professional work experience in machine learning, artificial intelligence, and machine learning algorithm development
Knowledge of cloud-based infrastructure, such as AWS, for machine learning based application development
Knowledge of various AI/ML concepts such as computer vision, image processing, statistical modeling/inference, data mining, natural language processing (NLP), prompt engineering, graph/geometric deep learning, large language models (LLM), and generative AI
Ability to operate a Vector Database
Ability to program in TypeScript and Python
Ability to pre-train and fine tune large language models including recent generative set models

Nice To Haves

Prior professional work experience as a software architect or in a technical leadership position
Knowledge of security best practices and compliance standards
Prior professional work experience in a start-up organization

Responsibilities

Deliver machine learning solutions by designing and developing models for complex web applications while ensuring adherence to best practices and architectural standards
Develop next generation algorithms to understand visual and textual content along with user interactions on the platform
Create classification models that include text, image, and videos along with developing supervised and semi-supervised models that scale to hundreds of millions of sources and their content.