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Data Annotation Research Jobs in Washington (NOW HIRING)

Omm IT Solutions

Senior Data Scientist

Ellicott City, MD · On-site

... annotation tools and semantic frameworks. * Ability to clean and process large amounts of real ... Experience working in an analytical research environment. * Experience in parallel processing such ...

iNovex Information Systems

Data Scientist 3

Annapolis, MD · On-site

$161K - $211K/yr

... annotation of language data with parts of speech information, and improve existing models by ... Research, or Computer Science or a degree in a related field (Computer Information Systems ...

iNovex Information Systems

Data Scientist 3

Annapolis, MD · On-site

$161K - $211K/yr

... annotation of language data with parts of speech information, and improve existing models by ... Research, or Computer Science or a degree in a related field (Computer Information Systems ...

Seekr

Senior Data Scientist

Reston, VA · On-site

Coordinate data collection and annotation efforts for supervised training efforts * Design and implement tests for machine learning algorithm effectiveness and performance monitoring * Research and ...

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Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
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What cities in Washington are hiring for Data Annotation Research jobs? Cities in Washington with the most Data Annotation Research job openings:
Data Annotation Research jobs near you
Sr. Researcher - GeoInt AI/ML Enabled Spatiotemporal Imagery

Sr. Researcher - GeoInt AI/ML Enabled Spatiotemporal Imagery

Bluemont Technology & Research, Inc.

Bethesda, MD • On-site

Full-time

Posted 4 days ago

Job description

JOB TITLE: Sr. Researcher - GeoInt AI/ML Enabled Spatiotemporal Imagery
LOCATION: Bethesda, Maryland
CLEARANCE: MUST process current TS/SCI with polygraph
PROGRAM GOAL: Aims to develop re-identification methods that autonomously associate objects across diverse, non-collaborative, video sensor footage, to distill raw pixel data into spatiotemporal motion vectors, providing the ability to analyze these patterns for anomalies and threats. This includes the creation of models of "normal" human movement across times, locations, and people in order to characterize what makes an activity detectable as anomalous within the expanding corpus of global human trajectory data.
JOB RESPONSIBILITIES:
a) Primary responsibility is to serve as the SME (Subject Matter Expert) / SETA (Scientific, Engineering, and Technical Assistance) for the Program.
b) Attend meetings, workshops, conferences and testing events as a Subject Matter Expert.
c) Assist with the development of presentations such as Program Management Reviews.
d) Serve as a Liaison between Performers, Test & Evaluation contributors, Government and Transition partners.
e) Review, provide analysis, and make recommendations concerning technical reports, data and Performer approaches.
f) Examine data sources and literary sources for emerging technology related to the Program.
g) Provide technical support and expertise on new concepts (seedlings) beyond the Program within areas of expertise.
h) Knowledge of development and testing tools for Program.
i) May work to define collections/storage cloud architectures for the Program.
j) Other tasking as assigned (e.g. you may provide technical review of similar Programs).
REQUIRED EXPERTISE:
• Current TS/SCI (Tier 5+) with polygraph
• Bachelors' degree in physics, mathematics, computer science, or relevant engineering fields (e.g. electrical, computer, systems, software) with eight plus (8+) years of work experience, or Masters' degree with four plus (4+) years of work experience, or PhD with two plus (2+) years of work experience. PhD is desirable, but not absolutely required if work experience provides depth and breadth of technical understanding and evidence of problem-solving capability equivalent to what would be expected for a PhD.
• Five (5) years of experience in computer vision R&D.
• Two (2) years of experience with R&D of machine learning and deep learning algorithms.
• One (1) year of experience managing a multi-disciplinary research and development (R&D) or Test and Evaluation (T&E) team.
• Two (2) years of experience creating program plans, work breakdown structures, and milestone schedules.
• Excellent writing and editing skills. Ability to develop succinct, comprehensive, understandable documents using complex data from multiple sources.
• Excellent slide development and PowerPoint skills. Ability to visually communicate complex ideas at a high level for technically savvy, but non-expert audiences.
• Strong organizational, problem solving, and time management skills. Must be detail oriented.
• Ability to proactively manage multiple, concurrent tasks.
• At least 4 of the qualifications listed in Desired Expertise.
• Experience in the Intelligence Community (IC) or Department of Defense (DoD), including experience with requirements, CONOPS and research technology transition.
DESIRED EXPERTISE (in order of importance):
• Experience with architectures to support large spatiotemporal data management and processing.
• Experience with the institutional review board (IRB) process for human subjects' research and IRB approved video collection.
• Experience with development in the Open Media Processing Framework (OpenMPF).
• Experience with deployment of computer vision analytics in a large-scale framework.
• Experience managing/performing large-scale video collection, curation and annotation.
• Experience with video collection from fixed security/surveillance, airborne (e.g. drone, UAV), and ground mobile (e.g. cell phone, auto mounted, etc.) video sensors.
• Experience with image or video frame geo-localization.
Bluemont Technology & Research, Inc. (Bluemont) offers a premium benefits package. Our culture is based on treating people like you would treat yourself. The company is focused on challenging applications of cutting-edge technologies and data intensive applications. Bluemont maintains a drug-free workplace and performs background checks.
Bluemont is an E-Verify Employer. Follow this link to view: www.dhs.gov/E-Verify

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