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Image Annotation Jobs in Washington, DC (NOW HIRING)

Knowledge and experience in biomedical informatics, image processing, and natural language ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

Knowledge and experience in biomedical informatics, image processing, and natural language ... Experience in content development and/or text annotation (e.g., annotation of certain types of ...

... value behind the image. Your expertise will help improve how mission data is identified ... Experience with AI/ML training data creation, annotation, validation, review, or Structured ...

... value behind the image. Your expertise will help improve how mission data is identified ... Experience with AI/ML training data creation, annotation, validation, review, or Structured ...

Showing results 21-40

Image Annotation information

See Washington, DC salary details

$860

$2.4K

$3.5K

How much do image annotation jobs pay per week?

As of Sep 11, 2026, the average weekly pay for image annotation in Washington, DC is $2,396.60, according to ZipRecruiter salary data. Most workers in this role earn between $1,763.46 and $2,982.69 per week, depending on experience, location, and employer.

What is an image annotation?

An Image Annotation job involves labeling or tagging objects, regions, or features within images to train machine learning models. Annotators use various techniques, such as bounding boxes, polygons, or key points, to define elements in images. This work is essential for tasks like object detection, image segmentation, and facial recognition. Image annotation helps improve AI accuracy in applications such as autonomous vehicles, medical imaging, and security systems.

What are the key skills and qualifications needed to thrive in image annotation, and why are they important?

To thrive as an Image Annotation professional, attention to detail, strong visual perception, and accuracy are essential, often complemented by a high school diploma or relevant experience in data labeling or computer vision projects. Familiarity with annotation tools such as LabelImg, CVAT, or Supervisely, and a basic understanding of file formats and image labeling standards are typically required. Excellent communication, time management, and the ability to focus on repetitive tasks help individuals excel in this position. These skills ensure high-quality annotated data, which is critical for training reliable machine learning and AI models.

What are some common challenges faced by image annotation specialists in their daily work?

Image annotation specialists often encounter challenges such as maintaining accuracy and consistency when labeling large volumes of images, especially when object boundaries are ambiguous or vary across images. The need to meet tight project deadlines while ensuring high-quality output can be demanding, and handling repetitive tasks may require sustained focus and attention. Collaboration with machine learning engineers or project managers is common, as they may provide feedback or clarification on annotation guidelines. Despite these challenges, working in image annotation offers the opportunity to contribute directly to cutting-edge AI technologies and gain valuable experience in the growing field of computer vision.

What are the most commonly searched types of Image Annotation jobs in Washington, DC?

The most popular types of Image Annotation jobs in Washington, DC are:

What are popular job titles related to Image Annotation jobs in Washington, DC?

For Image Annotation jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Image Annotation jobs in Washington, DC look for?

The top searched job categories for Image Annotation jobs in Washington, DC are:

Infographic showing various Image Annotation job openings in Washington, DC as of September 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $124,623 per year, or $59.9 per hour.

Artificial Intelligence / Machine Learning Developer

Ashburn, VA • On-site

$127K - $190K/yr

Full-time

Re-posted 4 days ago


Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com. We are seeking an Artificial Intelligence/Machine Learning Developer to join our team and support our federal customer.Qualified applicants may be subject to a security investigation and must meet minimum qualifications for access to classified information. This is a highly technical position; individuals will be screened by peers in a technical review of skills and experience.Essential Duties and Responsibilities:Drive a big data approach to execute government requirements to manage, prepare, analyze, and enrich image, biometric, and related mission data to gather new insights.As the AI/ML Developer, work as part of a team to provide consultative, architectural, program, and engineering support for a federal customer.This is a client-facing position working on-site as per the requirements established by the DHS customer.Develop, train, evaluate, fine-tune, and deploy advanced AI/ML, computer vision, deep-learning, and GenAI models.Design and implement innovative AI solutions to address complex business challenges using techniques such as computer vision, image analysis, image classification, object detection, image segmentation, image matching, facial recognition, facial verification, biometric analysis, natural language processing, and large language models.Prepare image, biometric, and related datasets for model development, including data extraction, cleaning, normalization, annotation, labeling, augmentation, feature engineering, data balancing, and training/validation/test-set construction.Develop, train, evaluate, and improve image-analysis and computer-vision models used for biometric, identity-resolution, image-quality, matching, classification, detection, segmentation, or related mission capabilities.Optimize model performance, ensuring accuracy, efficiency, scalability, bias awareness, and operational reliability.Evaluate model performance using appropriate measures, including precision, recall, F1 score, confusion matrices, ROC-AUC, mean average precision, false-match rates, false-non-match rates, false acceptance rates, false rejection rates, latency, throughput, and related performance metrics.Develop and maintain user-friendly AI applications and interfaces, including image-analysis tools, analytic dashboards, chatbots, virtual assistants, and generative content tools.Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.Stay up to date with the latest advancements in AI/ML and emerging technologies, such as computer vision, biometrics, generative AI, reinforcement learning, and secure AI deployment.Conduct research and experiments to explore new AI techniques and applications, including image-model training, computer-vision model evaluation, prompt engineering, advanced RAG, image retrieval, multimodal models, and fine-tuning LLMs.Ensure compliance with data privacy, biometric-data handling, security, and governance requirements, especially when working with sensitive data, images, biometric information, and generative-AI outputs.This role will be responsible for briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior levels of management.Work Experience and Job Skills:Three (3) or more years of experience in the Information Technology field focusing on AI/ML engineering projects, computer vision, image analysis, biometric technologies, MLOps, DevSecOps, and technical architecture.Demonstrated hands-on experience developing, training, fine-tuning, evaluating, or deploying computer-vision, image-analysis, deep-learning, or biometric AI/ML models.Experience working with image-analysis use cases such as image classification, object detection, image segmentation, image matching, face detection, facial recognition, facial verification, image quality assessment, liveness detection, identity verification, fingerprint analysis, iris recognition, or related technologies.Familiarity with biometric systems, biometric matching, identity resolution, facial recognition, fingerprint, iris, liveness detection, or image-quality analysis is required.Proficiency in developing, deploying, and fine-tuning generative-AI models, including large language models (LLMs).Strong proficiency in programming languages such as Python, R, Java, and C/C++.Experience with machine-learning, deep-learning, computer-vision, and generative-AI frameworks.Proficiency in ML modeling frameworks and libraries such as scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, YOLO, Detectron, Hugging Face, or equivalent platforms.Experience with natural-language-processing techniques, including text classification and language generation.Experience developing and evaluating image-analysis models using image transformations, feature extraction, embeddings, image-data augmentation, annotation/labeling, and model-performance metrics.Solid understanding of any cloud platform, such as AWS, Azure, or GCP, and deployment strategies for AI/ML, image-analysis, and computer-vision workloads.Solid understanding of MLOps and DevSecOps practices for deploying AI/ML, computer-vision, and image-analysis models and applications.Proficiency in front-end development technologies such as React, Angular, Vue.js, HTML, CSS, and JavaScript.Knowledge of database systems, such as SQL, NoSQL, vector databases, graph databases, and data-warehousing concepts.An understanding and competency surrounding data storage, access, ingestion, and loading.Databases: PostgreSQL, NoSQL, vector databases, graph databases, or comparable technologies.ETL/ELT concepts.Data warehouse concepts.SQL.Competency in data exploration, analytics, data quality, image-data processing, and feature engineering.Python experience with Pandas, NumPy, Polars, PySpark, OpenCV, Pillow, scikit-image, or comparable data and image-processing tools.Experience with Plotly, Matplotlib, or equivalent data-visualization tools.Knowledge of data encoding, normalization, regularization, image preprocessing, data augmentation, and related data-preparation methods.Understanding of deep-learning concepts and architectures such as CNNs, RNNs, LSTMs, GANs, transformers, vision transformers, and multimodal models, with the ability to apply them to real-world image, biometric, and mission datasets.Proficiency in NLP tools such as SpaCy, Thinc, Gensim, or comparable frameworks.Knowledge of GenAI tools, including Hugging Face models, OpenAI models, Grok, or comparable platforms.General competency in various ML disciplines, including image classification, object detection, segmentation, facial recognition, biometric matching, forecasting, transformers, generative AI, anomaly detection, deep learning, and pattern recognition.Enthusiastic, proactive, positive attitude with great listening skills, high integrity, and the ability to work effectively in a team environment.Adaptability to changing priorities and a willingness to learn and grow are essential.Excellent organizational skills and the ability to effectively manage concurrent projects.Comprehensive problem-solving skills with exceptional attention to detail.Ability to learn, evolve, think creatively, and work proactively.Ability to work under pressure at times and to be extremely flexible with changing priorities.Ability to work independently and in a team setting, take ownership of and complete relatively complex tasks, effectively using available resources, with minimal guidance.Education:Bachelor's Degree in Computer Science, Information Technology Management, Engineering, Data Science, Artificial Intelligence, Computer Vision, Mathematics, Statistics, Physics, or another related technical field is preferred. Alternative work-related experience, military duty, and/or specialized or higher education may be substituted.Certificates, Licenses and Registrations:This federal program requires candidates to be United States Citizens.Must have an active DHS clearance.Any related systems engineering, computer vision, biometrics, data science, machine learning, cloud, or technical certifications are desired.AWS/Azure/GCP AI/ML certifications are preferred but not required.Communication Skills:Must have excellent written and verbal communication skills.Ability to convey technical information-including model performance, image-analysis results, biometric matching limitations, and AI/ML solution tradeoffs-to non-technical individuals.Demonstrated experience communicating effectively across internal and external organizations.Must work well in a matrixed team environment.Travel:On-site in Ashburn, VA.Environmental Requirements:Mainly sedentary; in an office environment.May be required to lift up to ten (10) pounds.Flexible in working extended hours.The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions.Please note: Candidate(s) will be required to go through pre-employment screening.Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets) 
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