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Contract Data Annotation Jobs in Washington (NOW HIRING)

BIM Manager (Bentley)

Fairfax, VA · On-site

$99K - $127K/yr

... common data environments, support disciplined model integration and clash detection workflows, and help produce precise, contract-compliant digital deliverables. This position is ideal for a ...

As a Transportation Model Manager, you will proactively manage model health and common data ... Support digital delivery requirements by preparing precise, contract-compliant deliverables for ...

Showing results 21-27

Contract Data Annotation information

What is a contract data annotation?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

What are the key skills and qualifications needed to thrive as a contract data annotation specialist?

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

Is data annotation still hiring?

Data annotation roles are currently in demand as companies continue to develop AI and machine learning models. Many positions are available for remote work, often requiring basic computer skills and attention to detail, with some roles offering flexible schedules. Job availability can vary by industry and region, so checking specific job boards is recommended.

Is it hard to get hired for contract data annotation?

Contract data annotation jobs are generally accessible to individuals with basic computer skills and attention to detail. The hiring process often involves completing a skills test or sample annotation task, and some roles may require familiarity with specific tools or platforms. Competition can vary depending on the demand and the company's requirements, but many positions are available for entry-level candidates.

What are the most commonly searched types of Data Annotation jobs in Washington?

The most popular types of Data Annotation jobs in Washington are:

What are popular job titles related to Contract Data Annotation jobs in Washington?

For Contract Data Annotation jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Contract Data Annotation jobs in Washington look for?

The top searched job categories for Contract Data Annotation jobs in Washington are:

What cities in Washington are hiring for Contract Data Annotation jobs?

Cities in Washington with the most Contract Data Annotation job openings:

Infographic showing various Contract Data Annotation job openings in Washington as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Computational Biologist (AI/ML) - Essex Management (Contingent Roles)

Rockville, MD • On-site

Full-time

Medical, Retirement

Re-posted 13 days ago


Job description

Overview
Job Title: Computational Biologist (AI/ML)- Essex Management (Contingent Roles)
Notice to Candidates: Employment in these positions is expressly contingent upon Essex Management's receipt of a contract award from the Federal Government.
Location
US Remote
About Essex
This position supports "Essex, an Emmes Company". Essex is a biomedical informatics and health information technology-focused consultancy founded in 2009 and headquartered in Rockville, MD. The Essex team comprises experts with extensive experience in strategically developing and managing complex health and biomedical information programs for clients in the Federal Government, research academia, and private sectors.
Primary Purpose
The Computational Biologist (AI/ML) is a role within the Bioinformatics Department of the BIDS Division at Essex. This role brings meaningful scientific and technical expertise to the design, execution, and delivery of bioinformatics work across federal biomedical research programs. The Computational Biologist (AI/ML) owns well-defined tasks and small projects with minimal supervision and contributes substantively to team problem-solving and scientific quality. This role specifically focuses on applying Artificial Intelligence, Machine Learning and Deep Learning to bioinformatic analysis, and thus the ideal candidate is expected to leverage traditional bioinformatic techniques as well as emerging techniques. Essex supports programs in precision oncology, cancer genomics, clinical data infrastructure, and translational research, and the Computational Biologist (AI/ML) is expected to bring scientific judgment and technical capability to the work, not just execution.
Responsibilities
Core Functions
  • Own and execute well-defined analytical and technical tasks and small projects with minimal supervision from senior staff or your manager.
  • Assist Associate Informaticists with task-related questions, troubleshooting, and orientation.
  • Contribute substantively to team discussions on methodology, standards, tools, and technical decisions.
  • Apply working familiarity with best practices in your domain to deliver scientifically sound, high-quality work products.
  • Support peer review of deliverables and contribute to quality assurance activities.
  • Contribute to team documentation, SOPs, and knowledge base materials.
  • Shadow senior staff during candidate interviews to begin developing evaluation skills.
  • Participate in internal training sessions, brown bags, and knowledge-sharing activities.
  • Perform other related duties as assigned.

Role-Specific Functions
  • Design and implement AI/ML models applied to biomedical data, including genomic, proteomic, and multimodal clinical datasets, to support precision oncology and translational research.
  • Apply large language models, retrieval-augmented generation (RAG) techniques, and graph neural networks to make biomedical data interoperable and AI-ready.
  • Develop, test, and optimize pipelines for variant calling and annotation leveraging modern ML workflows and frameworks.
  • Curate, model, and integrate genetic and clinical datasets into standardized, interoperable formats to support precision medicine programs.
  • Generate high-quality, interpretable reports for internal and external stakeholders that translate complex AI/ML outputs into actionable scientific and clinical insights.

Qualifications
Required skills
Core Skills
  • Working proficiency in the core technical tools, analytical approaches, and data standards relevant to the assigned program and department.
  • Ability to work independently and within a team in a fast-paced, collaborative environment.
  • Strong written and oral communication skills, including the ability to document work clearly and present findings to technical audiences.
  • Proficiency with Microsoft Office applications.

Role-Specific Skills Core Skills
  • Proficiency in Python and SQL; demonstrated experience with ML frameworks (PyTorch, TensorFlow) and code versioning (Git).
  • Strong background in machine learning and AI, including deep learning architectures (CNNs, GNNs) applied to biomedical or complex multi-modal datasets.
  • Familiarity with genetic variant standards (HGVS, VCF) and clinical data ontologies.
  • Demonstrated ability to work cross-functionally and communicate technical results clearly to diverse scientific and clinical audiences.

Required experience
Core Experience
  • Bachelor's degree or advanced degree in bioinformatics, computational biology, data science, genetics, biology, health informatics, clinical research, or a related field.
  • 2 to 5 years of relevant professional or research experience.

Role-Specific Experience
  • Demonstrated success applying AI/ML to biomedical or multi-modal datasets (genomics, proteomics, clinical).
  • Track record of publications or applied innovation in AI-driven data science for life sciences preferred.
  • Experience applying LLMs or RAG approaches to scientific or clinical data problems preferred.

Why work at Emmes?
At Emmes, your actions and hard work will have a direct impact on public health initiatives, both globally and in our local communities with opportunities for volunteerism through our Emmes Cares community engagement program. We offer a competitive benefits package focused on the health and needs of our growing workforce, including:
  • Flexible Approved Time Off

  • Tuition Reimbursement

  • 401k Retirement Plan
  • Work From Home Anywhere in the US

  • Maternal/Paternal Leave

  • Casual Dress Code & Work Environment

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The Emmes Company, LLC is an equal opportunity employer and does not discriminate in its selection and employment practices. All qualified applicants will receive consideration for employment without regard to disability or protected veteran status.
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