pay
Required Skills
LLMs
Pipeline integration
Data analytics
Scaled-analysis judgment
Data science
About micro1
micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.
Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.
Role Title: Data Science & Analytic Methodology SME
Role Type: Contractor
Location: Remote
micro1 is engaging Data Science & Analytic Methodology SMEs to contribute expertise to a customer's high-impact project focused on advanced analytic pipelines and large language models (LLMs). 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
Map scaled-analysis and pipeline-integration scenarios to an established taxonomy across key evaluation areas.
Author detailed analytic cases that reflect authentic deployment patterns, including automated triage, enrichment, and analysis-at-scale, as well as representative failure modes in real-world settings.
Evaluate and grade responses based on criteria such as source handling, reasoning, understanding of limitations, and practical utility.
Identify and flag instances of model over-refusal that could hinder legitimate analytic workflows or disrupt pipeline continuity.
Document challenging edge cases, emerging methodology concerns, and provide actionable recommendations for continuous improvement.
Contribute clear, insightful written and verbal feedback that supports iterative, high-quality project outcomes.
Preferred Qualifications
Demonstrated experience integrating LLMs—such as government GPT variants—into complex data or analytic pipelines.
Proven capability in conducting analysis at scale, with an understanding of automation failure modes and relevant evaluation metrics.
Track record of teaching, mentoring, or technical leadership in data science or related analytic disciplines.
Expertise in authoring clear, concise technical documentation and conveying complex concepts through strong written English.
Exposure to the design of evaluation frameworks or benchmark systems.
Familiarity with defense, intelligence, or government analytic domains is highly valued.
Ability to operate effectively in distributed, international project environments with minimal clearance constraints.
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