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From Home Ai Data Rater information

What is the difference between From Home Ai Data Rater vs From Home Content Moderator?

AspectFrom Home Ai Data RaterFrom Home Content Moderator
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI training, data labelingOnline platforms, social media moderation
Common Search IntentData annotation, AI training jobsContent review, community moderation jobs

Both roles are remote and require similar skills, but From Home Ai Data Raters focus on labeling data to train AI systems, while From Home Content Moderators review online content to ensure community guidelines are followed. The roles differ mainly in their purpose within the tech industry, with data raters supporting AI development and content moderators maintaining platform integrity.

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From Home Ai Data Rater jobs near you
Infographic showing various From Home Ai Data Rater job openings in Kansas as of July 2026, with employment types broken down into 70% Full Time, 26% Part Time, and 4% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution.
AI Data Strategy Engineer / Applied Scientist, LLM Data

AI Data Strategy Engineer / Applied Scientist, LLM Data

Propio

Leawood, KS • On-site

Full-time

Posted 20 days ago

Propio rating

6.1

Company rating: 6.1 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

370th of 487 rated business services

Job description

Job Summary:
Propio Language Services is a provider of high-quality interpretation, translation, and localization services. They are seeking an AI Data Strategy Engineer / Applied Scientist, LLM Data to manage the data strategy and workflows that enhance their multilingual AI systems. The role involves overseeing the entire AI data lifecycle, from acquisition to evaluation, ensuring the quality and effectiveness of the data used in AI applications.
Responsibilities:
• Define the end-to-end data roadmap for multilingual and multimodal AI systems, including text, speech, translation, interpretation, low-resource languages, and agentic AI workflows.
• Design and build dataset curation pipelines for training, post-training, and evaluation, including cleaning, deduplication, filtering, PII redaction, quality scoring, sampling, balancing, and versioning.
• Create annotation schemas, labeling guidelines, QA rubrics, golden datasets, and reviewer workflows for multilingual, speech, translation, and agentic AI data.
• Build evaluation datasets and benchmarks, analyze model failure modes, and translate performance gaps into targeted data improvements.
• Support post-training data workflows such as SFT, instruction tuning, preference data, RLHF/DPO-style data, reward model data, and synthetic data generation.
• Use modern annotation tools and AWS-based data infrastructure to scale secure, traceable, and compliant AI data workflows.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Machine Learning, Data Science, Computational Linguistics, Linguistics, Statistics, or a related field, or equivalent practical experience.
• 4+ years of experience in AI data, ML data operations, NLP data engineering, applied ML, speech/translation data, or LLM data workflows.
• Strong hands-on experience with Python, SQL, and dataset curation pipelines.
• Experience with annotation workflows, QA rubrics, evaluation datasets, or human-in-the-loop data processes.
• Familiarity with multilingual NLP, speech data, translation data, low-resource languages, conversational AI, or agentic AI datasets.
• Working knowledge of AWS data and ML tools such as S3, Glue, SageMaker, Bedrock, Lambda, Step Functions, EKS/ECS, IAM, or KMS.
• Strong communication skills and ability to work with ML engineers, applied scientists, product teams, linguists, data teams, and vendors.
Preferred:
• Master’s or PhD in Computer Science, Machine Learning, NLP, Computational Linguistics, Data Science, Statistics, or a related field.
• Experience with LLM post-training workflows such as SFT, instruction tuning, preference data, RLHF, DPO, reward modeling, or evaluation data generation.
• Experience with synthetic data generation, active learning, weak supervision, LLM-as-judge workflows, or automated data quality scoring.
• Experience with modern annotation and data platforms such as Labelbox, Scale AI, Prodigy, Argilla, Snorkel, Humanloop, or custom internal tooling.
Company:
Propio is a mobile platform that provides financial management services for small business owners. Founded in 2022, the company is headquartered in Washington, USA, with a team of 2-10 employees. The company is currently Early Stage.

What Propio employees say

Pay

Benefits

Hours and flexibility

Workplace

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