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Remote Machine Vision Engineer Jobs in Alexandria, VA

We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from ... Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available) Responsibilities

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... The position also emphasizes experience with Computer Vision, NLP, Deep Learning, LLMs, Agentic AI ...

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... The position also emphasizes experience with Computer Vision, NLP, Deep Learning, LLMs, Agentic AI ...

Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and established 1099 options (no c2c ... The position also emphasizes experience with Computer Vision, NLP, Deep Learning, LLMs, Agentic AI ...

Comprehensive Health & Benefits - Medical, dental, and vision coverage to keep you and your family ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Senior Machine Learning Engineer

Arlington, VA ยท On-site +1

$120K - $165K/yr

You'll implement novel embeddings-based change detection and advanced computer vision techniques ... Practical knowledge of remote sensing, satellite imagery, or related geospatial domains * Knowledge ...

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Remote Machine Vision Engineer information

See Alexandria, VA salary details

$33.7K

$137.8K

$207.1K

How much do remote machine vision engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for remote machine vision engineer in Alexandria, VA is $137,823.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,600.00 and $165,900.00 per year, depending on experience, location, and employer.

What does a remote machine vision engineer do?

A Remote Machine Vision Engineer designs, develops, and implements computer vision systems that enable machines to interpret visual information, often working from a remote location. Their tasks include creating algorithms for image processing, integrating hardware like cameras, and collaborating with teams to solve automation or inspection challenges. They may work in industries such as manufacturing, robotics, or healthcare, using technologies like deep learning and neural networks. Remote Machine Vision Engineers typically use tools such as Python, OpenCV, and TensorFlow, and communicate with their teams via digital platforms. This role requires both strong programming skills and a deep understanding of image analysis techniques.

What are the key skills and qualifications needed to thrive as a remote machine vision engineer?

To thrive as a Remote Machine Vision Engineer, you need expertise in computer vision, image processing, programming (such as Python or C++), and a relevant engineering or computer science degree. Familiarity with frameworks like OpenCV, deep learning libraries (TensorFlow or PyTorch), and experience with cloud-based collaboration tools are typically required. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in this role. These skills ensure the accurate design and deployment of vision solutions while maintaining productivity and collaboration in a remote work environment.

How do remote machine vision engineers typically collaborate with cross-functional teams given the remote nature of the role?

Remote Machine Vision Engineers often work closely with software developers, hardware engineers, and project managers through virtual meetings, collaborative platforms, and shared code repositories. Effective communication is essential to ensure alignment on project goals, technical specifications, and integration challenges. Regular video conferences, clear documentation, and agile project management tools help maintain productivity and foster team cohesion, despite being geographically dispersed.

What are popular job titles related to Remote Machine Vision Engineer jobs in Alexandria, VA?

For Remote Machine Vision Engineer jobs in Alexandria, VA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Vision Engineer jobs in Alexandria, VA look for?

The top searched job categories for Remote Machine Vision Engineer jobs in Alexandria, VA are:

What cities near Alexandria, VA are hiring for Remote Machine Vision Engineer jobs?

Cities near Alexandria, VA with the most Remote Machine Vision Engineer job openings:

Infographic showing various Remote Machine Vision Engineer job openings in Alexandria, VA as of August 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 100% Remote job distribution, with an average salary of $137,823 per year, or $66.3 per hour.

Machine Learning Engineer

Chantilly, VA โ€ข On-site, Remote

NT Concepts
IT Servicesย โ€ขย 51 - 200 employees

Full-time

Posted 5 days ago


Job description

ย 

We are seeking aย Machine Learning Engineerย with a passion for building mission-critical capabilities to join our talent network. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, explore What's Next with us.

Mission Focus: Our machine learning teams bridge the gap between cutting-edge AI research and operational government missions. We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from early research and prototyping all the way into stable, scalable production environments.

ย 

In this role, you will help design, build, and deploy automated ML workflows that directly support national security analysts and operators. We embrace modern agile practices, a DataOps/DevSecOps/MLOps ethos to "automate-first," and modern cloud-native architectures.

Clearance:ย Activeย TS/SCIย required (CI Polygraph preferred or must be eligible to obtain)

Location/Flexibility: Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available)

Responsibilitiesย 

  • Prototype to Production:ย Support the full machine learning lifecycle, taking computer vision models from experimentation and notebooks into containerized, high-throughput production microservices.
  • Mission Alignment:ย Work closely with mission partners, domain experts, and technical teams to understand real-world operational challenges and translate them into practical ML requirements.
  • MLOps & Pipeline Automation:ย Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD).
  • Model Development & Tuning:ย Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks (e.g., object detection, classification, segmentation, tracking).
  • System Integration:ย Collaborate with cross-functional software engineers and cloud architects to integrate ML models cleanly into larger enterprise systems and secure cloud infrastructures.
  • Optimization & Governance: Optimize inference performance, apply secure coding practices, and monitor models for drift and reliability once deployed.ย 

ย Qualifications

  • Clearance:ย Activeย TS/SCIย clearance.
  • Hands-On Experience:ย Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments.
  • Deep Learning & CV:ย Strong programming skills inย Pythonย and hands-on experience with deep learning frameworks (primarilyย PyTorch, OpenCV, TensorFlow, or NumPy).
  • ML Lifecycle & MLOps:ย Practical familiarity with containerization (Docker, Kubernetes) and ML lifecycle/pipeline platforms (e.g.,ย MLflow, Kubeflow, AWS SageMaker).
  • Cloud & DevOps Foundations:ย Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices (Git, CI/CD pipelines, Agile methodologies).
  • Customer & Mission Mindset:ย Ability to understand the end-user's mission objectives, iterate based on user feedback, and clearly communicate technical approaches.ย 

Preferred / Desired Skills:

  • Experience working within secure, air-gapped, or classified cloud environments (e.g., AWS GovCloud / C2S).
  • Experience with synthetic data generation techniques or multi-modal models.
  • Exposure to Large Language Models (LLMs) or generative AI workflows.
  • Familiarity with distributed model training and GPU resource management.ย 

Physical Requirements

  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 10-15 pounds at times.

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