Reviewing AI-generated technical documents such as design docs, pipeline documentation and API specs for correctness. Suits engineers and ML practitioners who have written these documents and can judge tradeoffs.
About the role
About This Opportunity
We're working with a leading foundational AI lab to find experienced machine learning engineers who can help train their latest language model on professional document, spreadsheet, and slide deck tasks.
We're looking for machine learning engineers with 4+ years building software, AI/ML systems, or data infrastructure in a professional engineering or data role to create, evaluate, and refine AI-generated documents, spreadsheets, and slide decks across core workflows: technical design documents and architecture decision records, data pipeline and ETL documentation, model evaluation and AI system readiness reports, API specification and integration guides, data quality and validation test plans, and developer onboarding guides and system architecture diagrams.
Compensation: $80/hour
Commitment: Flexible, 5-20 hours per week (or more if desired)
Qualifications
4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs for engineering or cross-functional stakeholders
Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail
About Ethos
Ethos is a new expert network built by a McKinsey/SoftBank/DeepMind team and backed by world-leading investors like General Catalyst. We connect experts with investors and consultancies for paid expert calls, speaking engagements, and advisory opportunities.
Key Requirements
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