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AI Data Strategy Engineer – Applied Scientist, LLM Data

Data EngineerData EngineerFull TimeRemoteSeniorTeam 1-10H1B No SponsorCompany SiteLinkedIn

Location

Kansas

Posted

5 days ago

Salary

0

Seniority

Senior

Bachelor Degree4 yrs expEnglishAWSPythonSQL

Job Description

AI Data Strategy Engineer – Applied Scientist, LLM Data

Propio Aruba Realty

• 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.

Job Requirements

  • 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.

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