ROLE SUMMARY:

As an early-career Engineer on the Image & Computer Vision AI team, you will support the development and deployment of computer vision capabilities that power Babel Street's intelligence applications. You will help build systems that extract, analyze, and reason over visual data, including image search, object and scene understanding, facial matching workflows, geolocation support, and multimodal intelligence features.

This role is well suited for someone with foundational experience in computer vision, image processing, machine learning, or applied AI who is ready to grow in a hands-on engineering environment. You will work with senior engineers and cross-functional partners to implement, test, and improve reliable 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.

ROLE FOCUS;

This role spans three practical execution areas:

Computer Vision & Image Analytics

You will help implement and maintain image analytics pipelines that support facial matching, object detection, scene understanding, and image similarity. This includes supporting image preprocessing, feature extraction, model inference, evaluation, and performance improvements under the guidance of more senior team members.

Geospatial & Location Inference from Imagery

You will assist with capabilities that infer location, context, or environmental attributes from imagery by using visual cues, metadata, and learned representations. This may include supporting image-based geolocation, landmark recognition, and contextual scene analysis used in intelligence workflows.

Multi-Modal AI & Image Search

You will contribute to multimodal AI systems that combine vision models with LLMs, embeddings, and retrieval pipelines to support natural-language search and reasoning over images and image collections. You will help integrate visual understanding into broader intelligence applications and workflows, including supporting entity and event extraction from image-based intelligence data.

KEY RESPONSIBILITIES:

• Assist in building and maintaining computer vision pipelines for image ingestion, preprocessing, inference, and evaluation.
• Support facial matching and identity-related vision workflows in accordance with accuracy, safety, and compliance requirements.
• Help develop, test, and improve 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.
• Support multimodal workflows that connect visual understanding with entity and event extraction, helping identify people, places, objects, activities, and relevant contextual signals from image-based intelligence data.
• Write clean, maintainable Python code and contribute to production services, APIs, and internal tools.
• Assist with model evaluation, bias testing, accuracy monitoring, and documentation for vision systems.
• Help optimize inference pipelines for performance, scalability, and cost efficiency, including GPU usage, batching, and model selection.
• Collaborate with Product, AI, and Engineering teams to integrate vision capabilities into user-facing intelligence applications.

QUALIFICATIONS:

Required

• 0-2 years of experience in computer vision, image processing, applied machine learning, or related academic/project work.
• Foundational understanding of computer vision models and techniques, such as CNNs, vision transformers, feature embeddings, or image classification.
• Exposure to image analytics such as facial recognition, object detection, image similarity, or related computer vision applications.
• Programming experience in Python and familiarity with common CV/ML libraries such as PyTorch, TensorFlow, OpenCV, or similar tools.
• Basic understanding of machine learning fundamentals, model evaluation, and performance tradeoffs.
• Experience working with image datasets through coursework, internships, research, open-source contributions, or professional projects.
• Ability to work collaboratively in a fast-moving, mission-driven engineering environment.

Preferred

• Exposure to facial matching or biometric systems, including through coursework, research, or project experience.
• Exposure to image-based geolocation, landmark recognition, scene analysis, or location inference.
• Familiarity with multimodal AI systems, including combining vision models with LLMs, embeddings, or natural-language search.
• Familiarity with entity extraction, event extraction, or related NLP/multimodal information extraction workflows.

EDUCATION:

Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field required, or equivalent practical experience through internships, research, bootcamps, open-source work, or professional projects.
Advanced degree is a plus but not required.

Benefits at Babel Street (just to name a few...)

• Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances - for you and your family!
• Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
• Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
• Holidays: Babel Street provides employees with 12 paid Federal Holidays
• Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.

Range for this position based on qualifications and experience

$85,000-$100,000 USD