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Data Annotation Research Jobs in Bothell, WA (NOW HIRING)

Experience with data annotation, scientific dataset evaluation, or quality assurance workflows * Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL * Background in research ...

3D Data Annotator

Seattle, WA · On-site

$90K - $130K/yr

The company leverages over a decade of advanced research in robotics and machine learning, as well ... Maintain strict adherence to annotation guidelines to ensure high standards of data quality and ...

Comfort with structured data annotation and rubric-based scoring * Prior work in trust and safety, content moderation, QA, or security research * Subject matter expertise in any high-risk domain ...

... research, and operations. What You'll Accomplish In your first 90 days, you'll... * Build fluency in mpathic's AI safety, human data, red teaming, annotation, QA, and evaluation workflows * Support ...

You will be instrumental in leveraging Lexion's state-of-the-art AI to research, design, and deploy ... Experience with language annotation and other forms of data markup for ML systems * Experience with ...

You will be instrumental in leveraging Lexion's state-of-the-art AI to research, design, and deploy ... Experience with language annotation and other forms of data markup for ML systems * Experience with ...

... Vision AI, data-centric AI, and applied ML. * Opportunity to contribute to research that directly impacts real-world AI products and services. * Access to proprietary datasets, annotation ...

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Data Annotation Research information

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.

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.

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 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.

What are popular job titles related to Data Annotation Research jobs in Bothell, WA? For Data Annotation Research jobs in Bothell, WA, the most frequently searched job titles are:
What cities near Bothell, WA are hiring for Data Annotation Research jobs? Cities near Bothell, WA with the most Data Annotation Research job openings:

Applied Physics

Alignerr

Seattle, WA • Remote

Full-time

Posted 22 days ago


Job description

Applied Physics - AI Data Trainer
About the Role
What if your deep expertise in physics could directly shape how AI understands the fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models - exposing gaps in their physical reasoning and helping ensure they never violate the principles of conservation of energy, momentum, or anything else your training tells you is non-negotiable.
This is a fully remote, flexible contract role built for researchers and scientists who want high-impact work on their own schedule. No prior AI experience required - just a command of physics that goes all the way down to first principles.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 10-40 hours/week
  • What You'll Do
    • Design Advanced Physics Problems
      - Craft open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics
    • Author Gold-Standard Solutions
      - Write rigorous, step-by-step "golden responses" with flawless handling of physical constants, unit conversions, and mathematical derivations
    • Audit AI Reasoning
      - Evaluate AI-generated proofs and simulations for physical consistency, identifying where models hallucinate results or violate first principles
    • Refine Model Behavior
      - Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints
    • Document Failure Modes
      - Systematically record where and how AI reasoning breaks down so research teams can address root causes
    • Who You Are
      • Completed or nearly completed PhD in Applied Physics, Physics, Engineering Physics, or a closely related field
      • Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
      • Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English
      • Uncompromising precision with units, scientific notation, and the logical structure of proofs
      • Self-directed and reliable - comfortable working independently on technical tasks without hand-holding
      • No prior AI or machine learning experience required
      Nice to Have
      • Experience with data annotation, scientific dataset evaluation, or quality assurance workflows
      • Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL
      • Background in research publication, technical writing, or academic instruction
      Why Join Us
      • Work on some of the most technically demanding AI projects in existence alongside world-leading research labs
      • Fully remote and asynchronous - work when and where it suits you
      • Freelance autonomy with the structure of meaningful, high-value technical work
      • Rare opportunity to apply your physics expertise beyond academia in a high-impact, forward-looking field
      • Potential for ongoing work and contract extension as new projects launch