AI Data Strategy Engineer – Applied Scientist, LLM Data

This is a fully remote position, open to applicants in Kansas.

📋 Description

• Outline the comprehensive data roadmap for multilingual and multimodal AI systems, encompassing text, speech, translation, interpretation, low-resource languages, and agentic AI workflows.

• Develop and implement dataset curation pipelines for training, post-training, and evaluation, which include processes such as cleaning, deduplication, filtering, PII redaction, quality scoring, sampling, balancing, and versioning.

• Establish annotation schemas, labeling guidelines, quality assurance rubrics, golden datasets, and reviewer workflows tailored for multilingual, speech, translation, and agentic AI data.

• Construct evaluation datasets and benchmarks, assess model failure modes, and convert performance deficiencies into focused data enhancements.

• Assist in post-training data workflows including SFT, instruction tuning, preference data, RLHF/DPO-style data, reward model data, and synthetic data generation.

• Leverage modern annotation tools and AWS-based data infrastructure to expand secure, traceable, and compliant AI data workflows.

⛳️ Requirements

• Bachelor's degree in Computer Science, Machine Learning, Data Science, Computational Linguistics, Linguistics, Statistics, or a related discipline, or equivalent practical experience.

• Over 4 years of experience in AI data, machine learning data operations, NLP data engineering, applied machine learning, speech/translation data, or LLM data workflows.

• Proficient hands-on experience with Python, SQL, and dataset curation pipelines.

• Experience with annotation workflows, quality assurance 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 machine learning tools such as S3, Glue, SageMaker, Bedrock, Lambda, Step Functions, EKS/ECS, IAM, or KMS.

• Excellent communication skills and the ability to collaborate with ML engineers, applied scientists, product teams, linguists, data teams, and vendors.

🏝️ Benefits

• Comprehensive health coverage.

• Flexible work arrangements.

• Opportunities for professional development and growth.

• Collaborative and innovative work environment.