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Computer Engineer Jobs in Springfield, VA (NOW HIRING)

Image & Computer Vision AI Engineer

Reston, VA

$116K - $136.80K/yr

Image & Computer Vision Ai Engineer Hatch I.T. is partnering with Babel Street to find an Image & Computer Vision AI Engineer. Please see details below: As an engineer on the Image & Computer Vision ...

Applied Computer Vision Engineer (TS/SCI)

Herndon, VA · On-site

$114.70K - $135.20K/yr

We need a Computer Vision (CV) engineer to work on the full stack of the CV workflow, to include acquiring and standardization of imagery data, designing experiments and developing CV models, testing ...

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$50.7K

$127.1K

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How much do computer engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for computer engineer in Springfield, VA is $127,105.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $137,500.00 per year, depending on experience, location, and employer.

What Is a Computer Engineer?

A computer engineer designs, researches, tests, and develops computer equipment and software such as circuit boards, chips, routers, and application programs. Computer engineers analyze complex equipment and systems to understand the best way to improve it. They create new types of information technology devices and use logic and reasoning to hone in on goals, test assumptions, and identify the strengths and weaknesses of alternative solutions to problems. Engineers often work in teams and have to be able to communicate with other types of engineers, including non-technical team members. Computer engineers make sure that components fit together properly and function according to the latest software developments.

What are the key skills and qualifications needed to thrive as a Computer Engineer, and why are they important?

To thrive as a Computer Engineer, you need a strong background in computer science, mathematics, and hardware/software design, typically supported by a bachelor’s degree in computer engineering or a related field. Familiarity with programming languages (such as C/C++ or Python), circuit design tools, and industry certifications like CompTIA or Cisco are highly valuable. Problem-solving, teamwork, and effective communication are essential soft skills that set top performers apart. These abilities ensure that computer engineers can design, implement, and optimize systems that meet technical requirements and business goals.

What are common challenges computer engineers face when working on cross-functional teams?

Computer engineers often collaborate with software developers, hardware designers, and project managers, which can present challenges in aligning technical requirements and communication styles. Ensuring that everyone has a clear understanding of system limitations and integration points is crucial, as miscommunication can lead to project delays or rework. Staying adaptable and proactively clarifying expectations helps computer engineers navigate these collaborative environments successfully.

What are computer engineers?

Computer engineers are professionals who design, develop, test, and maintain computer hardware and software systems. They work at the intersection of electrical engineering and computer science, focusing on how computer systems function and how they can be improved. Their roles can involve creating microprocessors, designing circuit boards, developing embedded systems, and optimizing software for hardware performance. Computer engineers play a crucial role in advancing technology across industries, from consumer electronics to aerospace and healthcare.

What is the difference between Computer Engineer vs Software Developer?

AspectComputer EngineerSoftware Developer
Required CredentialsBachelor's in Computer Engineering or related field; certifications like Cisco, CompTIABachelor's in Computer Science or Software Engineering; certifications like Microsoft, AWS
Work EnvironmentDesigning hardware, embedded systems, and software integration in labs or officesWriting, testing, and maintaining software applications in offices or remote setups
Employer & Industry UsageTech companies, manufacturing, telecommunications, embedded systemsIT firms, software companies, startups, enterprise software development

Computer Engineers focus on both hardware and software systems, often working on embedded systems and hardware integration. Software Developers primarily create and maintain software applications. While their roles overlap in programming, Computer Engineers have a broader scope including hardware design, whereas Software Developers specialize in software solutions.

What are the most commonly searched types of Computer Engineer jobs in Springfield, VA? The most popular types of Computer Engineer jobs in Springfield, VA are:
What job categories do people searching Computer Engineer jobs in Springfield, VA look for? The top searched job categories for Computer Engineer jobs in Springfield, VA are:
What cities near Springfield, VA are hiring for Computer Engineer jobs? Cities near Springfield, VA with the most Computer Engineer job openings:
Infographic showing various Computer Engineer job openings in Springfield, VA as of May 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $127,105 per year, or $61.1 per hour.
Image & Computer Vision AI Engineer

Image & Computer Vision AI Engineer

Hatchit Co

Reston, VA

$116K - $136.80K/yr

Other

Posted 10 days ago


Job description

Image & Computer Vision Ai Engineer

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

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 their Reston, VA/Washington DC office or their Somerville MA office.

Babel Street is the trusted technology partner for the world'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. The actionable insights we deliver safeguard lives and protect critical assets around the world.

Role Focus:

This role spans three practical execution areas:

Computer Vision & Image Analytics

You will implement and operate 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.

Geospatial & Location Inference from Imagery

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

Multi-Modal AI & Image Search

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.

What you will do:

  • 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.

What you will bring:

Required

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

Preferred

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

Education:

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

$140,000 - $170,000 a year