Senior AI Software Engineer – Remote (Part-Time)

Crossing Hurdles; United States; Remote; CAD 241,000 - 343,000; Part time

Job summary

Crossing Hurdles is seeking a Senior Software Engineer to work on a contractor assignment focused on Python/TypeScript-based pipelines for AI data generation, collection, and evaluation. This remote, part-time role requires 20–40 hours per week with at least 4 hours overlap during PST business hours.

You will collaborate with researchers and engineers to refine evaluation rubrics, label data, and translate qualitative findings into scalable processes, finishing with clear write-ups and

Qualifications

• 5+ years building and maintaining pipelines or infrastructure.
• Hands-on experience with preference data collection and rubric creation.
• Experience navigating or contributing to large codebases; VSCode is a plus.
• Experience with AI/LLM evaluation or related engineering workflows is preferred.
• LinkedIn profile is mandatory for review.
• Candidates should not currently be working with Microsoft.

Responsibilities

• Build and maintain pipelines and infrastructure supporting AI data generation, collection, and evaluation workflows.
• Design, refine, and iterate on rubrics and evaluation criteria for preference data.
• Review and label preference data while identifying subtle quality issues.
• Collaborate with researchers and engineers to translate qualitative judgment into scalable evaluation processes.
• Synthesize technical findings into clear, actionable write-ups, updates, and recommendations.

Skills

Python

TypeScript

Golang

JavaScript

Preference data collection

Rubric creation

Tools

VSCode

Job description

Crossing Hurdles is seeking a Senior Software Engineer to work on a contractor assignment focused on Python/TypeScript-based pipelines for AI data generation, collection, and evaluation. This remote, part-time role requires 20–40 hours per week with at least 4 hours overlap during PST business hours.

You will collaborate with researchers and engineers to refine evaluation rubrics, label data, and translate qualitative findings into scalable processes, finishing with clear write-ups and