Image & Computer Vision AI Engineer

As an Engineer on the Image & Computer Vision AI team, you will play a hands-on role in developing and deploying computer vision capabilities that support Babel Street’s intelligence applications. You will build systems that extract, analyze, and reason over visual data—enabling facial matching, object and scene understanding, geolocation and location inference from imagery, and multimodal intelligence workflows. 

This role is execution-focused and suited for engineers with strong foundations in computer vision, image processing, and machine learning who want to apply their skills to real-world, mission-driven problems. You will work closely with AI, Product, and Engineering teams to deliver reliable, scalable, and cost-efficient vision capabilities, including integration with multimodal LLM systems that allow users to search and reason over images using natural language. 

This is a hybrid role to be based out of either our Reston, VA/Washington DC office or our Somerville MA office.

This role spans three practical execution areas: 

• →Build and maintain computer vision pipelines for image ingestion, preprocessing, inference, and evaluation. 

• →Implement facial matching, and identity-related vision workflows in accordance with accuracy, safety, and compliance requirements. 

• →Develop and support object detection, image similarity, and scene understanding models. 

• →Contribute to image-based geolocation and location inference capabilities using visual features and contextual signals. 

• →Support multimodal AI workflows that combine image embeddings with LLM-based search and reasoning. 

• →Write clean, maintainable Python code and contribute to production services and APIs. 

• →Assist with model evaluation, bias testing, and accuracy monitoring for vision systems. 

• →Optimize inference pipelines for performance, scalability, and cost efficiency (GPU usage, batching, model selection). 

• →Collaborate with Product and Engineering teams to integrate vision capabilities into user-facing intelligence applications. 

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required. 
Advanced degree is a plus but not required.