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Remote Machine Vision Engineer Jobs in Washington, DC

YO AI Labs

Senior Software Engineer - Remote

Washington, DC · Remote

$138K - $182K/yr

Senior Software Engineer Job Type: Contract Location: Remote Job Summary: In this role, you'll ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Knexus

AI Software Engineer (Remote)

Vienna, VA · Remote

... Engineer with 6-8 years of experience to join our AI applications team. This is a fully remote ... This role involves leveraging cutting-edge technologies, including GenAI and machine learning ...

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Showing results 21-40

All JobsMachine Vision Engineer JobsRemote Machine Vision Engineer JobsRemote Machine Vision Engineer Jobs in Washington, DC

Remote Machine Vision Engineer information

See Washington, DC salary details

$35.7K

$145.8K

$219.2K

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

As of Aug 18, 2026, the average yearly pay for remote machine vision engineer in Washington, DC is $145,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $175,600.00 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 Washington, DC?

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

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

The top searched job categories for Remote Machine Vision Engineer jobs in Washington, DC are:

Remote Machine Vision Engineer jobs near you
Infographic showing various Remote Machine Vision Engineer job openings in Washington, DC as of July 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 100% Remote job distribution, with an average salary of $145,843 per year, or $70.1 per hour.

Software Engineer (Full Stack) - SME

GRVTY

Springfield, VA • Remote

Full-time

Re-posted 25 days ago

Job description

What Impact You'll Have:

Join a mission-focused team where your work directly supports critical national security objectives. We are seeking a Subject Matter Expert (SME) Full Stack Developer to lead the design, development, and delivery of scalable, mission-driven applications within an ML/Ops environment. This role combines deep technical expertise with advanced system-level thinking and close collaboration across engineering, data science, and customer stakeholder teams.

The Full Stack Developer will perform rapid application design, ETL, data analysis, and interpretation while developing rules and methodologies for data collection and analysis. You will architect, develop, and maintain a Python-based data warehouse processing system that serves as the backend for a user-facing application, while also leading development of modern GUI applications using REST APIs and contemporary web frameworks.

You will work closely with data scientists, computer vision engineers, ETL engineers, and intelligence analysts to integrate machine learning capabilities into production systems, enabling scalable model deployment, monitoring, and continuous improvement. This role emphasizes ownership, technical leadership, and delivery of production-ready solutions that operate reliably in dynamic, real-world environments.

What You'll Be Owning:

Lead and participate in the architectural design of complex features early in the development lifecycle.
Translate customer requirements and roadmap priorities into technical solutions, tasks, timelines, and resource plans.
Develop, integrate, and maintain full stack applications supporting ML/Ops pipelines and data-driven systems.
Design and implement scalable APIs and services to support machine learning model deployment and inference.
Develop and maintain data pipelines, ETL processes, and data storage solutions for large-scale datasets.
Collaborate with data scientists and ML engineers to operationalize models within production environments.
Optimize application and system performance for scalability, reliability, and efficiency, including edge and distributed environments when applicable.
Conduct peer reviews and establish coding standards to improve overall code quality and maintainability.
Guide development testing, exploratory testing, automated testing, and validation strategies.
Own code in production environments, respond to incidents, and lead root cause analysis and continuous improvement efforts.
Ensure security, compliance, and governance are maintained throughout the development lifecycle.
Perform technical planning, system integration, verification and validation, and risk assessments across system components.
Mentor and develop junior and mid-level engineers, fostering technical growth and high-performing teams.
Drive adoption of modern ML/Ops practices, tools, and automation frameworks across the team.

What You Must Have:

Active TS/SCI clearance with the ability to obtain a CI poly
Bachelor's degree in Computer Science, Engineering, or a related technical field.
14+ years of professional experience in full stack software development.
Expert-level proficiency in Python and object-oriented design patterns.
Extensive experience developing backend systems, APIs, and data processing pipelines.
Strong experience with modern web development frameworks, including React.js, Node.js, and/or Electron.
Deep understanding of data modeling techniques and experience working with large-scale and time series datasets.
Experience with relational and non-relational databases such as PostgreSQL, MongoDB, and BigQuery.
Experience building and maintaining RESTful APIs and microservices architectures.
Experience supporting machine learning workflows, including model integration, deployment, and monitoring.
Familiarity with ML/Ops tools and utilities such as MLflow, DVC, and/or Optuna.
Strong experience with Python libraries such as NumPy and Pandas.
Experience with Python web frameworks such as Flask, FastAPI, Pydantic, Gunicorn, and Uvicorn.
Experience with containerization and DevOps practices, including Docker and CI/CD pipelines.
Experience with web servers such as Apache and Nginx.
Experience working within Agile development environments and using associated tools.

What Would be Nice to Have:

Experience supporting government or defense-related programs.
Experience integrating computer vision or machine learning capabilities into operational systems.
Knowledge of real-time data processing, streaming architectures, or distributed systems.
Experience with cloud-based ML/Ops environments and infrastructure (AWS, Azure, or Google Cloud Platform).
Experience with parallelization and multiprocessing frameworks such as Dask.
Knowledge of geospatial data processing tools and libraries including GeoPandas, Shapely, Rasterio, QGIS, and ArcPy.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
Experience with remote procedure call technologies such as gRPC and JSON-RPC.

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