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Machine Learning Object Detection Jobs in Reston, VA

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Build robust model monitoring, logging, and alerting systems to track performance and detect drift.

Ai Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Build robust model monitoring, logging, and alerting systems to track performance and detect drift.

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Build robust model monitoring, logging, and alerting systems to track performance and detect drift.

Core4ce

Quantum Engineer SME

Springfield, VA

$86K - $114K/yr

Apply principles, methods, and knowledge of functional areas (quantum machine learning and related ... object detection, image classification, synthetic image generation, anomaly detection or graph ...

Core4ce

Quantum Engineer SME

Springfield, VA · On-site

$86K - $114K/yr

Apply principles, methods, and knowledge of functional areas (quantum machine learning and related ... object detection, image classification, synthetic image generation, anomaly detection or graph ...

NT Concepts

Data Scientist

Herndon, VA · On-site +1

... object detection robustness. Working within a cross-functional team and reporting to a technical lead, you will operate across the machine learning development lifecycle, from data curation and ...

NT Concepts

Data Scientist

Chantilly, VA · On-site

... Machine Learning, Computer Vision, and Object Detection. • Experience building and maintaining ETL pipelines, including Kubeflow pipelines. • Hands-on experience with imagery data, overhead ...

NT Concepts

Data Scientist

Chantilly, VA · On-site

... Machine Learning, Computer Vision, and Object Detection. • Experience building and maintaining ETL pipelines, including Kubeflow pipelines. • Hands-on experience with imagery data, overhead ...

Varsity Tutors

Machine Learning Tutor

Rockville, MD · Remote

$40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Washington, DC · Remote

$40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

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All JobsMachine Learning Object Detection JobsMachine Learning Object Detection Jobs in Reston, VA

Machine Learning Object Detection information

See Reston, VA salary details

$32.8K

$134K

$201.3K

How much do machine learning object detection jobs pay per year?

As of Jun 23, 2026, the average yearly pay for machine learning object detection in Reston, VA is $133,966.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $161,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Object Detection Engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.
What cities near Reston, VA are hiring for Machine Learning Object Detection jobs? Cities near Reston, VA with the most Machine Learning Object Detection job openings:
Machine Learning Object Detection jobs near you
Machine Learning Engineer

Machine Learning Engineer

AI Squared

Washington, DC

Other

Posted 2 days ago

Job description

Machine Learning Engineer
Washington, DC (Hybrid)

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.

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