Machine Learning Research Expert

$115/hr

rate as listed

Workload: 10+ hrs/week
Location: Location not stated
Field: STEM and Coding

Author and solve realistic machine learning research problems based on experiment design, ablations, model evaluation and failure analysis. This remote contract role is intended for experienced researchers rather than engineers focused primarily on deployment or data infrastructure.

The work

Contractors turn situations from their own machine learning research into rigorous evaluation problems. Day-to-day work includes defining an experimental question, specifying controls and ablations, interpreting model behavior, producing a reference answer with step-by-step reasoning, and identifying methodological errors that may appear plausible to a non-practitioner.

What afterquery screens for

The screening focuses on verifiable research experience, including at least three years of full-time ML research after your degree, hands-on experimental work, and the ability to reason precisely about evaluation design and failure analysis. Strong Python and experience with a deep learning framework such as PyTorch or JAX are required. Publications at venues such as NeurIPS, ICML, ICLR, ACL or CVPR, and experience in an industry research lab or university research group, are preferred. Clear written English is also preferred.

Working arrangement

The work is fully remote and asynchronous, with no fixed schedule. You must be able to commit at least 10 hours per week, while setting your own hours and scaling your workload up or down from week to week. Payments are made weekly via Stripe.

Pay band: $115/hr

What they look for

Master's or PhD in computer science, statistics, mathematics or a related field
At least 3 years of full-time ML research after the qualifying degree
Hands-on experiment design, ablation studies and model evaluation
Python programming for machine learning research
PyTorch or JAX
Research failure analysis and step-by-step technical writing

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 checks whether your graduate qualification is in an accepted field and whether you have at least three years of post-degree research, excluding PhD study while including eligible postdoctoral work.
A strong answer: Give the degree, field, institution and completion date, then provide a dated sequence of full-time research positions with concise descriptions of the ML research conducted. Separate PhD years from post-degree employment so the qualifying experience can be verified directly.
Where people lose it: Candidates lose points by counting PhD research toward the three-year requirement or by describing software engineering roles without identifying any original ML research responsibilities.

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

Rates by specialty, the platforms hiring, and every open role in this field.