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Assisted Ai Training Jobs in Bothell, WA (NOW HIRING)

F5, Inc.

AI Engineer

Seattle, WA · On-site

Lead end-to-end model lifecycle: data pipelines, training, evaluation, fine-tuning, validation ... assisted tooling. * Stable, low-latency ML services with clear observability and alerting ...

Blue Origin

AI Engineer III - Blue Ring

Seattle, WA · On-site

$65.50 - $88/hr

... and AI-assisted decision-making that enable a small operations team to manage an entire satellite ... training and deploying time-series ML models on real spacecraft telemetry. Role and ...

Blue Origin, LLC

AI Engineer III - Blue Ring

Seattle, WA · On-site

$65.50 - $88/hr

... and AI-assisted decision-making that enable a small operations team to manage an entire satellite ... training and deploying time-series ML models on real spacecraft telemetry. Role and ...

Axon

Senior Agentic AI Research Scientist

Seattle, WA · On-site +1

$112K - $142K/yr

Lead end-to-end research efforts in AI-assisted universal search of and reasoning over large ... training or inference workflows, evaluation and ranking optimization, agentic tool use, and ...

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Showing results 21-40

All JobsAssisted Ai Training JobsAssisted Ai Training Jobs in Bothell, WA

Assisted Ai Training information

See Bothell, WA salary details

$39.7K

$107.6K

$148.1K

How much do assisted ai training jobs pay per year?

As of Aug 8, 2026, the average yearly pay for assisted ai training in Bothell, WA is $107,620.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,100.00 and $147,600.00 per year, depending on experience, location, and employer.

What is the difference between Assisted Ai Training vs Data Annotator?

AspectAssisted Ai TrainingData Annotator
Required CredentialsBasic technical skills, understanding of AI conceptsAttention to detail, basic computer skills
Work EnvironmentCollaborative, often remote, with AI development teamsRemote or on-site, focused on data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI and ML models

Assisted Ai Training involves guiding AI systems through training processes, often requiring some technical understanding. Data Annotators focus on labeling and preparing data for AI models. While both roles support AI development, Assisted Ai Training typically involves more technical interaction with AI systems, whereas Data Annotators primarily handle data labeling tasks.

Are there legitimate assisted AI training jobs?

Assisted AI training jobs are legitimate roles where workers help improve AI systems by providing data labeling, annotation, or feedback. These positions often require attention to detail, familiarity with AI tools, and sometimes specific certifications, and they are commonly found through reputable job platforms. However, job seekers should verify the legitimacy of employers to avoid scams.

How do I start a career in assisted AI training?

To start a career in assisted AI training, focus on developing skills in data annotation, machine learning concepts, and programming languages like Python. Gaining experience with labeling datasets, understanding AI models, and using annotation tools can improve your prospects; some roles may require a relevant degree or certification in computer science or data science.
Assisted Ai Training jobs near you
Infographic showing various Assisted Ai Training job openings in Bothell, WA as of August 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 100% In-person job distribution, with an average salary of $107,620 per year, or $51.7 per hour.

Clinician (Oncology / Hematology)

micro1 AI

Renton, WA • Remote

$160 - $200/hr

Part-time

Posted 4 days ago

Job description

Role Title: Clinician (Oncology / Hematology)


Role Type: Contractor


Location: Remote


micro1 is engaging Clinician (Oncology / Hematology)s to contribute to a customer’s project at the forefront of AI in healthcare. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Author and review evaluation tasks that require nuanced clinical judgment, leveraging Clinical Study Reports, periodic safety reports, and regulatory correspondence in oncology and haematology.
  2. Assess the clinical defensibility of efficacy and safety conclusions, ensuring endpoints and effect sizes reflect true clinical significance.
  3. Apply advanced judgment to dose escalation, dose-limiting toxicity, modifications, adverse event grading and attribution, and the coherence of patient narratives.
  4. Evaluate benefit-risk reasoning, scrutinizing the durability of conclusions in light of new events, and the realism of described management strategies.
  5. Identify and flag content that is clinically implausible or internally inconsistent, distinguishing these from legitimate clinical variation.
  6. Provide structured, guideline-based written rationales that clearly explain the validity or limitations of clinical interpretations for a non-clinical audience.


Preferred Qualifications

  1. Specialist registration or board certification in medical oncology and/or haematology, with 5+ years of post-training clinical experience.
  2. Direct involvement in clinical trials as investigator, sub-investigator, or sponsor-side medical monitor, safety physician, or clinical development physician.
  3. Proficiency with CTCAE grading, relevant response criteria (RECIST, Lugano, IMWG, IWCLL, ELN), and outcome endpoints (ORR, DoR, PFS, OS, MRD).
  4. Hands-on experience with trial documents such as protocols, investigator brochures, CSRs, safety narratives, or DSMB/IDMC materials.
  5. Demonstrated excellence in written communication, with clear, structured explanations of clinical reasoning tailored for non-clinical readers.
  6. Previous roles in medical monitoring or as medical director on oncology or haematology programmes, and committee participation (IDMC, DSMB, adjudication, or independent review committees).
  7. Peer-reviewed publication record or authorship on clinical trial manuscripts, with any exposure to AI-assisted clinical review tools seen as a plus.

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