Life Science Pod Lead

Crossing Hurdles; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Crossing Hurdles seeks a Life Science Pod Lead to guide a team of 5–10 trainers developing terminal-based life sciences tasks for AI training and evaluation. You will ensure scientific accuracy, reproducibility, and reliable automated grading.

Responsibilities include reviewing datasets and pipelines, validating results, designing workflows, and mentoring staff to maintain high-quality, scalable evaluation solutions.

Qualifications

• Ph.D., postdoctoral or equivalent life sciences research experience with strong computational expertise.
• Strong scientific programming skills, particularly Python.
• Previous experience as a pod lead.
• Expertise in bioinformatics, computational genomics, systems biology, biostatistics, drug discovery, structural biology or a related computational life sciences area.

Responsibilities

• Lead a pod of 5 to 10 technical trainers developing terminal-based life sciences tasks for AI training and evaluation.
• Review biological and clinical datasets, pipelines, environments, reference solutions and automated tests.
• Validate scientific assumptions, statistical methods and computational outputs.
• Design realistic multi-step workflows, reproducible solutions and objective grading criteria.
• Mentor trainers, allocate work, provide actionable feedback and track quality.

Skills

Python

Computational biology

Mentoring/leadership

Education

PhD or equivalent life sciences research

Strong computational expertise

Tools

Nextflow

Snakemake

Biopython

RDKit

HPC

Job description

Life Science Pod Lead

About the role

Lead a pod of 5 to 10 technical trainers developing terminal-based life sciences tasks for AI training and evaluation. Ensure scientific accuracy, reproducibility and reliable automated grading.

Responsibilities

• Review biological and clinical datasets, pipelines, environments, reference solutions and automated tests.
• Validate scientific assumptions, statistical methods and computational outputs.
• Design realistic multi-step workflows, reproducible solutions and objective grading criteria.
• Ensure appropriately licensed, de-identified data and review biosafety concerns.
• Mentor trainers, allocate work, provide actionable feedback and track quality.

Requirements

• Ph.D., postdoctoral or equivalent life sciences research experience with strong computational expertise.
• Strong scientific programming skills, particularly Python.
• Previous experience as a pod lead.
• Expertise in bioinformatics, computational genomics, systems biology, biostatistics, drug discovery, structural biology or a related computational life sciences area.
• Ability to independently validate scientific reasoning and computational results.

Preferred

• GATK, samtools, DESeq2, Seurat, Scanpy, Biopython, Nextflow, Snakemake, RDKit or medical imaging tools; Docker, Conda, Git, automated testing, HPC or AI evaluation experience.

Selection

Interest check form, assessment and delivery review.