Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading)

micro1 Inc.

United States

Remote

USD 55,000 - 96,000

Full time

4 days ago
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Job summary

micro1 Inc. is seeking a Softwood Lumber Grader / Sawmill Quality Supervisor (Visual Grading) on a contractor basis. The role is remote and focuses on applying specialized visual grading skills to train next-generation AI systems, evaluating softwood lumber for grade calls according to NLGA, WWPA, SPIB, and WCLIB rules.

You will document decision-making processes to support model training. Preferred candidates hold active certification as a softwood lumber grader or sawmill QC supervisor and

Qualifications

  • Active or recent certification as a softwood lumber grader or sawmill quality control supervisor from NLGA/WWPA/SPIB/WCLIB is preferred.
  • Demonstrated ability to interpret and apply industry grading rules with confidence and accuracy.
  • Experience providing written and verbal feedback or training on quality standards is a plus.

Responsibilities

  • Review and assess descriptions and images of sawn softwood lumber for accurate visual grading according to NLGA/WWPA/SPIB/WCLIB rules.
  • Identify and measure defects such as knots, wane, checks, shake, and warp, and determine grade limits.
  • Make clear grade calls on sample pieces based on rulebook criteria with written documentation of decisions.

Skills

Visual grading
Defect identification
Rulebook interpretation
Quality control documentation
Grade stamping familiarity

Job description

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
  1. Review and assess descriptions and images of sawn softwood lumber for accurate visual grading according to published rules (NLGA, WWPA, SPIB, WCLIB).
  2. Identify and measure lumber defects including knots, wane, checks, shake, and warp, and determine corresponding grade limits.
  3. Make clear grade calls on sample pieces based on rulebook criteria, documenting the decision-making process in writing.
  4. Evaluate grade stamping accuracy and provide feedback on proper application and compliance.
  5. Analyze grade recovery and quality control scenarios, offering insight into optimization possibilities.
  6. Reference the specific rule(s) that justify each grade decision, ensuring technical rigor.
  7. Deliver written and verbal explanations for decisions to support AI model training and development.
Preferred Qualifications
  1. Active or recent certification as a softwood lumber grader or sawmill quality control supervisor from a recognized agency (e.g., NLGA, WWPA, SPIB, WCLIB).
  2. Demonstrated expertise in visual lumber grading and defect identification across common softwood species.
  3. Proven ability to interpret and apply industry grading rules with confidence and accuracy.
  4. Experience providing written and verbal feedback or training on quality standards.
  5. Familiarity with grade stamping procedures, grade recovery metrics, and quality control best practices.
  6. Strong attention to detail, technical documentation skills, and ability to articulate decisions clearly.
  7. Recent practical experience in a sawmill environment is highly valued.
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