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From Home Computer Vision Postdoc Jobs in Virginia

Image & Computer Vision AI Engineer

Reston, VA ยท On-site

$119K - $143K/yr

Geospatial & Location Inference from Imagery You will contribute to capabilities that infer ... Build and maintain computer vision pipelines for image ingestion, preprocessing, inference, and ...

$69K/yr

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

What We Offer * Remote, work-from-home career * Average first-year earnings of $69K through ... Laptop or desktop computer with a working camera * Insurance license required or willingness to ...

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From Home Computer Vision Postdoc information

What are some common challenges faced by remote Computer Vision Postdocs, and how can they be addressed?

Remote Computer Vision Postdocs often encounter challenges such as limited access to lab hardware, potential isolation from peers, and coordinating collaborative research across time zones. To overcome these, postdocs can leverage cloud-based computational resources, schedule regular virtual meetings with their research team, and participate in online seminars or forums to stay connected with the community. Effective communication and proactive networking are key to maintaining productivity and collaboration while working from home.

What are From Home Computer Vision Postdocs?

A From Home Computer Vision Postdoc is a researcher with a doctoral degree who conducts advanced research in computer vision while working remotely, typically from home. These postdoctoral positions focus on developing algorithms and systems that enable computers to interpret and analyze visual information from the world, such as images and videos. Remote postdocs in this field often collaborate with academic institutions, research labs, or companies via digital communication tools. They may publish scientific papers, contribute to open-source projects, or assist in teaching while enjoying the flexibility of a work-from-home arrangement.

What are the key skills and qualifications needed to thrive as a From Home Computer Vision Postdoc, and why are they important?

To thrive as a From Home Computer Vision Postdoc, you need a PhD in computer science or a related field, with deep expertise in computer vision algorithms and research methodologies. Proficiency with programming languages like Python or C++, and experience using deep learning frameworks such as TensorFlow or PyTorch, are typically required. Strong analytical thinking, self-motivation, and effective remote collaboration skills help you excel in this role. These skills are crucial for conducting advanced research, publishing high-quality work, and contributing to collaborative projects in a remote academic or industry environment.
What are the most commonly searched types of Computer Vision Postdoc jobs in Virginia? The most popular types of Computer Vision Postdoc jobs in Virginia are:

Image & Computer Vision AI Engineer

Hatch IT

Reston, VA โ€ข On-site

Full-time

Posted 23 days ago


Job description

hatch I.T. is partnering with Babel Street to find an Image & Computer Vision AI Engineer.ย Please see details below:

About the Role

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 Streetโ€™s intelligence applications. You will build systems that extract, analyze, and reason over visual dataโ€”enabling facial matching, object and scene understanding, geolocation and location inference from imagery, and multimodal intelligence workflows.ย 

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.ย 

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

About the Company

Babel Street is the trusted technology partner for the worldโ€™s most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.ย  The actionable insights we deliver safeguard lives and protect critical assets around the world.ย ย Babel Street is headquartered inย Reston, Virginia, withย regionalย offices in Boston,ย MAย and Cleveland, OH, andย internationalย offices inย Australia, Canada, Israel, Japan, and the U.K.

Role Focus:

This role spans three practical execution areas:ย 

Computer Vision & Image Analyticsย 

You will implement andย operateย image analytics pipelines that support facial matching, object detection, scene understanding, and image similarity. This includes image preprocessing, feature extraction, model inference, evaluation, and performance optimization to meet mission-grade accuracy and latency requirements.ย 

Geospatial & Location Inference from Imageryย 

You will contribute to capabilities that infer location, context, or environmental attributes from imageryโ€”leveragingย visual cues, metadata, and learned representations. This includes supporting image-based geolocation, landmark recognition, and contextual scene analysis used in intelligence workflows.ย 

Multi-Modal AI & Image Searchย 

You will support multimodal AI systems that combine vision models with LLMs, embeddings, and retrieval pipelines to enable natural-language search and reasoning over images and image collections. You will help integrate visual understanding into broader intelligence applications and workflows.ย 

What you will do:
  • Build andย maintainย computer vision pipelines for image ingestion, preprocessing, inference, and evaluation.ย 
  • Implement facial matching, and identity-related vision workflowsย in accordance withย accuracy, safety, and compliance requirements.ย 
  • Develop and support object detection, image similarity, and scene understanding models.ย 
  • Contribute to image-based geolocation and location inference capabilities using visual features and contextual signals.ย 
  • Support multimodal AI workflows that combine image embeddings with LLM-based search and reasoning.ย 
  • Write clean, maintainable Python code and contribute to production services and APIs.ย 
  • Assistย with model evaluation, bias testing, and accuracy monitoring for vision systems.ย 
  • Optimizeย inference pipelines for performance, scalability, and cost efficiency (GPU usage, batching, modelย selection).ย 
  • Collaborate with Product and Engineering teams to integrate vision capabilities into user-facing intelligence applications.ย 
What you will bring:

Requiredย 

  • 3+ years of experience in computer vision, image processing, or applied machine learning.ย 
  • Hands-on experience with computer vision models and techniques (e.g., CNNs, transformers for vision, feature embeddings).ย 
  • Experience building or integrating image analytics such as facial recognition, object detection, or image similarity.ย 
  • Strong programming skills inย Python; experience with common CV/ML libraries (PyTorch, TensorFlow, OpenCV, etc.).ย 
  • Solid understanding of machine learning fundamentals, model evaluation, and performance tradeoffs.ย 
  • Experience working with large image datasets andย productionย ML pipelines.ย 
  • Ability to work collaboratively in a fast-moving, mission-driven engineering environment.ย 

Preferredย 

  • Experience withย facial matching or biometric systemsย in regulated or high-stakesย environments.
  • Experience withย image-based geolocationย or scene/location inference.
  • Familiarity withย multimodal AI systems, including combining vision models with LLMs or natural-language search.ย 

Education:

  • Bachelorโ€™s degree in Computer Science, Engineering, Data Science, orย a relatedย technical fieldย required.ย 
    Advanced degree is a plus but notย required.ย 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.