LLM Engineer (Data Generation)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Design, generate, evaluate, and iteratively improve training data to enhance next-generation generative AI model performance. Analyze model bottlenecks and failure cases with Research and Model Training teams to define data requirements across instruction, preference, reasoning, and domain-specific datasets. Build synthetic data generation pipelines, establish data quality and evaluation criteria (e.g., LLM-as-a-judge), and develop iterative filtering strategies to systematically improve dataset quality at scale.

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design and generate data to improve model performance, collaborating with Research and Model Training to define data requirements.
•Design, generate, and refine instruction, preference, reasoning, and domain-specific training datasets.
•Experimentally analyze how generated data affects model performance and iteratively improve data generation strategies.
•Build and operate data generation pipelines, including synthetic data automation and large-scale workflow execution.
•Define data quality and evaluation criteria and validate quality using LLM-as-a-judge, rule-based validation, and human feedback, then iterate via generation and filtering.

Key Requirements

•3+ years of experience in LLM, Machine Learning, or Data Generation-related work.
•General understanding of deep learning, machine learning, and natural language processing.
•Understanding of how training data is composed, preprocessed, evaluated for quality, and reflected into training.
•Strong capability in Python-based data processing and automation development.
•Experience handling, cleaning, filtering, and quality managing large-scale training datasets (or equivalent).

Experience:3+ yearsMachine learningData generationLLM

Skills:Problem-solvingCollaborationCommunication

Tech Stack:PythonLLMMachine LearningNatural Language ProcessingSynthetic DataLLM-as-a-JudgeRule-based ValidationHuman FeedbackPromptingDPORLHFRLAIFOpenAI EvalsLM Evaluation HarnessDeepEvalAirflowRaySparkTool CallingAgent

Company Brief

42dot

Website

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42dot

3 weeks ago

LLM Engineer (Data Generation)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design and generate data to improve model performance, collaborating with Research and Model Training to define data requirements.
•Design, generate, and refine instruction, preference, reasoning, and domain-specific training datasets.
•Experimentally analyze how generated data affects model performance and iteratively improve data generation strategies.
•Build and operate data generation pipelines, including synthetic data automation and large-scale workflow execution.
•Define data quality and evaluation criteria and validate quality using LLM-as-a-judge, rule-based validation, and human feedback, then iterate via generation and filtering.

Key Requirements

•3+ years of experience in LLM, Machine Learning, or Data Generation-related work.
•General understanding of deep learning, machine learning, and natural language processing.
•Understanding of how training data is composed, preprocessed, evaluated for quality, and reflected into training.
•Strong capability in Python-based data processing and automation development.
•Experience handling, cleaning, filtering, and quality managing large-scale training datasets (or equivalent).

Experience:3+ yearsMachine learningData generationLLM

Skills:Problem-solvingCollaborationCommunication

Company Brief

42dot

Website