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Data Annotation Biology Jobs in Kent, WA (NOW HIRING)

... with structured data annotation and rubric-based scoring • Prior work in trust and safety ... biology, medicine, law, finance, etc.) Company : Handshake is a college career network that helps ...

... biological, radiological, nuclear), cybersecurity, persuasion and influence operations, child ... Comfort with structured data annotation and rubric-based scoring * Prior work in trust and safety ...

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Showing results 1-20

Data Annotation Biology information

See Kent, WA salary details

$42.3K

$138.6K

$221.8K

How much do data annotation biology jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data annotation biology in Kent, WA is $138,558.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,200.00 and $153,500.00 per year, depending on experience, location, and employer.

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

AspectData Annotation BiologyData Labeling Specialist
Required CredentialsBiology degree or related certificationHigh school diploma or equivalent, training in labeling tools
Work EnvironmentLaboratory, research settings, or remoteOffice, remote, or data centers
Industry UsageBiotech, healthcare, researchTech, AI, machine learning
Job FocusAnnotating biological data, images, and sequencesLabeling various data types for AI models

Data Annotation Biology involves annotating biological data, often requiring a background in biology, while Data Labeling Specialists focus on labeling diverse data types for AI applications, with less emphasis on biological expertise. Both roles are essential in data preparation but serve different industry needs.

What is data annotation in biology?

Data annotation in biology involves labeling or tagging biological data—such as images, gene sequences, or medical records—with relevant information to make it useful for research and machine learning. Annotators may identify specific features, mark regions of interest, or classify data according to biological characteristics. This work is crucial for training artificial intelligence systems to recognize patterns, make predictions, and automate analyses in biological research. Annotated datasets help improve the accuracy and reliability of computational models in genomics, microscopy, drug discovery, and more.

What are the key skills and qualifications needed to thrive as a data annotation biology specialist, and why are they important?

To thrive as a Data Annotation Biology specialist, you need a solid background in biological sciences, attention to detail, and experience handling scientific datasets, often supported by a degree in biology or a related field. Familiarity with annotation tools, bioinformatics databases, and software such as BLAST or Ensembl is typically required, alongside knowledge of data management systems. Strong analytical thinking, precision, and good communication skills help you interpret complex biological data and collaborate effectively with researchers. These skills ensure the accuracy and utility of annotated datasets, which are critical for advancing biological research and data-driven discoveries.

What are the unique challenges faced by data annotators working with biological datasets, and how can they be addressed?

Data annotators in biology often encounter challenges such as dealing with complex, high-dimensional data (like gene sequences or microscopy images) and the need for a deep understanding of biological terminology and context. Errors in annotation can significantly impact downstream research or machine learning models, so maintaining accuracy is crucial. Collaborating closely with biologists and domain experts helps ensure consistency and correctness, while ongoing training and clear annotation guidelines help address ambiguities. Staying up-to-date with evolving biological standards and tools is also essential for success in this role.
What are popular job titles related to Data Annotation Biology jobs in Kent, WA? For Data Annotation Biology jobs in Kent, WA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Biology jobs in Kent, WA look for? The top searched job categories for Data Annotation Biology jobs in Kent, WA are:
Infographic showing various Data Annotation Biology job openings in Kent, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $138,558 per year, or $66.6 per hour.

AI Red Teamer (LLM Generalist)

Handshake

Seattle, WA • On-site

Full-time

Re-posted 17 days ago


Job description

Job Summary:
Handshake is a company focused on creating a path to great careers for everyone, and they are seeking an AI Red Teamer to stress-test large language models. The role involves designing adversarial prompts to expose vulnerabilities in AI models, thereby supporting AI safety and model robustness for leading research labs.
Responsibilities:
• Craft creative prompts and multi-turn scenarios to stress-test AI guardrails across diverse risk categories
• Discover ways around safety filters, restrictions, and defenses using jailbreak, evasion, and prompt injection techniques
• Explore edge cases to provoke disallowed, harmful, or incorrect outputs
• Evaluate and score model responses against structured harm taxonomies and severity rubrics
• Document experiments clearly, including what you tried, why you tried it, and what it revealed
• Review and refine adversarial prompts generated by other team members
• Contribute to harm taxonomy development, calibration exercises, and inter-rater reliability work
• Collaborate with engineers, data scientists, and researchers to share findings and strengthen defenses
• Work with potentially disturbing content on a regular basis (see Content Warning below)
• Stay current on jailbreaks, attack methods, and evolving model behaviors
Qualifications:
Required:
• Strong hands-on experience using multiple LLMs (ChatGPT, Claude, Gemini, open-source models, etc.)
• Intuition for crafting adversarial prompts; familiarity with jailbreak or evasion techniques is a strong plus
• Creative, adversarial problem-solving skills
• Clear and thoughtful written communication
• Strong ethical judgment and the ability to separate adversarial thinking from personal values
• Self-directed, collaborative, and comfortable in feedback-heavy environments
• Curiosity, persistence, and comfort with frequent failure in experimentation
Preferred:
• Familiarity with Python or other scripting languages
• Experience working with LLM APIs or evaluation tooling
• 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 (cybersecurity, chemistry, biology, medicine, law, finance, etc.)
Company:
Handshake is a college career network that helps students and recent graduates find their next opportunity. Founded in 2014, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.