Parallel Algorithms and HPC Researcher (Research Coding Tasks)

$80/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: STEM and Coding

Convert published parallel algorithms and HPC research into reproducible coding tasks for frontier AI agents. You will design hidden evaluations, implement reference and improved solutions, and review agent submissions against research benchmarks.

Work

Start from a recent paper with released code, ideally your own, and remove the implementation of its core contribution. You will package the remaining repository as a self-contained task in which an AI agent must reconstruct the missing work and outperform the paper's reported results on its own benchmarks.

Evaluation design

Each task requires a clear specification, held-out workloads, per-metric pass thresholds, a hidden reference implementation, and a second implementation demonstrating that the target can be beaten. You will later inspect agent attempts for correctness, performance, benchmark integrity, and unintended shortcuts.

Screening

The platform screens for a completed or in-progress PhD in computer science or a related field, published parallel algorithms or HPC research, and released code tied to at least one paper. Be prepared to discuss specific contributions, benchmark methodology, scaling behavior, and implementation decisions under follow-up. First-author work reporting measured improvements is preferred. Preferred depth areas are MPI, OpenMP, sparse linear algebra, parallel graph algorithms and GPU solvers, and comfort with Docker and reproducible benchmark setups is also preferred.

Logistics

This is fully remote, asynchronous contract work with flexible scheduling. Each task is expected to take a few hours, and candidates who provide the requested materials may be prioritised for review; the process also includes background checks.

Pay band: $80/hr

What they look for

PhD in computer science or a related field, completed or in progress
Published research in parallel algorithms or high-performance computing
Released code associated with at least one published paper
Research implementation experience in parallel algorithms and HPC
Benchmark design with held-out workloads and per-metric thresholds
Performance analysis and review of research-grade code

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether your research record, implementation ownership, publication details, and released artifact can be connected through specific, checkable evidence.
A strong answer: Identify the paper, venue, artifact link, authorship role, and the component you implemented. Distinguish your personal contribution from the broader team's work and name the benchmarks used.
Where people lose it: Candidates lose points by discussing a research area broadly while omitting a paper identifier, code link, or precise account of which implementation work was theirs.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

STEM AND CODING on Sidequest

What stem and coding AI work pays

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