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Biology AI Systems Trainer

Aqusag, LLC.
Remote
Remote

About this role

About the Role In this role, you'll apply your biology and AI/ML expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

What You'll Do

  • Leverage your biology domain expertise to evaluate, annotate, and benchmark AI systems in real-world computational biology use cases.
  • Assess the accuracy, relevance, and performance of AI-generated outputs in genomics, transcriptomics, and systems biology scenarios.
  • Apply advanced analytical reasoning to critically review scientific workflows and pipelines, identifying strengths and areas for improvement.
  • Collaborate with interdisciplinary teams, providing feedback on AI model performance based on biological context.
  • Document observations and findings with clarity, highlighting scientific rationale and actionable insights.
  • Communicate complex concepts effectively through both written and verbal channels to technical and non-technical stakeholders.
  • Stay current on emerging trends in computational biology, bioinformatics, and machine learning in biology.

What We're Looking For

  • PhD in Biology, Bioinformatics, or a closely related field, or equivalent industry/research experience.
  • Proven experience in data-driven biological research and computational analysis workflows.
  • Proficiency with scripting (Python, R, Bash) and scientific tools such as BWA, GATK, STAR, Salmon, Seurat, or Scanpy would be ideal.
  • Deep understanding of genomics, transcriptomics, structural biology, or systems biology is desirable.
  • Excellent scientific reasoning, analytical, and problem-solving abilities.
  • Strong written and verbal communication skills, with the ability to articulate findings and collaborate effectively.
  • Comfort working remotely and contributing to distributed teams.

Nice to Have

  • Experience with AI/ML or LLM evaluation in a biology context.
  • Hands-on experience with NGS pipelines, CRISPR workflows, AlphaFold, or PyMOL.
  • Published research or contributions to open-source projects in computational biology or bioinformatics.

Compensation & Benefits

  • Salary and benefits not disclosed.

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