Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading)

micro1; United States; Remote; USD 28,000 - 83,000; Full time

Job summary

micro1 is seeking a Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading) to support remote AI data training projects. You will apply expert NLGA/WWPA/SPIB/WCLIB rule-based grading to evaluate softwood lumber descriptions and images, determine grades, stamps, and QC outcomes.

Preferred candidates hold current or recent certification and can articulate decisions in writing and verbally; this is a remote contractor role delivering high-quality feedback to AI model training.

Qualifications

• Visual grading to published rules (NLGA, WWPA, SPIB, WCLIB)
• Ability to identify knots, wane, checks, shake and warp
• Experience with grade stamping procedures
• Experience providing written and verbal feedback on quality standards
• Ability to reference rulebooks to justify grade decisions

Responsibilities

• Review and assess lumber descriptions and images for accurate visual grading per NLGA/WWPA/SPIB/WCLIB
• Identify and measure defects such as knots, wane, checks, shake, and warp; determine grade limits
• Make clear grade calls and document decision-making process
• Evaluate grade stamping accuracy and provide feedback on compliance
• Analyze grade recovery and quality control scenarios for optimization
• Provide written and verbal explanations to support AI model training

Skills

Visual grading

Lumber defects identification

Grade stamping

Quality control

Rule-based decision making

Job description

Pay: $20 - $60/hour

Required Skills
Visual grading to published rules (NLGA - WWPA - SPIB - WCLIB)
Lumber defect identification and grade limits (knots - wane - checks - shake - warp)
Grade stamping
grade recovery and QC
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: Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading)

Role Type: Contractor

Location: Remote

micro1 is engaging Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading) experts to contribute their highly specialized visual grading skills and sawmill quality control experience to a customer's project. 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. The assignment focuses on evaluating and providing detailed, rule-based feedback on softwood lumber grades, defects, and quality control cases. If you have current or recent grading agency certification and hands‑on knowledge of NLGA, WWPA, SPIB, or WCLIB standards, this is an excellent opportunity to leverage your expertise while working remotely.

Scope of Work

Review and assess descriptions and images of sawn softwood lumber for accurate visual grading according to published rules (NLGA, WWPA, SPIB, WCLIB).
Identify and measure lumber defects including knots, wane, checks, shake, and warp, and determine corresponding grade limits.
Make clear grade calls on sample pieces based on rulebook criteria, documenting the decision‑making process in writing.
Evaluate grade stamping accuracy and provide feedback on proper application and compliance.
Analyze grade recovery and quality control scenarios, offering insight into optimization possibilities.
Reference the specific rule(s) that justify each grade decision, ensuring technical rigor.
Deliver written and verbal explanations for decisions to support AI model training and development.

Preferred Qualifications

Active or recent certification as a softwood lumber grader or sawmill quality control supervisor from a recognized agency (e.g., NLGA, WWPA, SPIB, WCLIB).
Demonstrated expertise in visual lumber grading and defect identification across common softwood species.
Proven ability to interpret and apply industry grading rules with confidence and accuracy.
Experience providing written and verbal feedback or training on quality standards.
Familiarity with grade stamping procedures, grade recovery metrics, and quality control best practices.
Strong attention to detail, technical documentation skills, and ability to articulate decisions clearly.
Recent practical experience in a sawmill environment is highly valued.
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