Job Description

Hiring a Technical Reviewer on behalf of a leading AI lab to evaluate and refine benchmarking pipelines for reinforcement learning (RL) environments and agentic AI systems. In this role, you'll be responsible for

reviewing environment design, terminal conditions, and evaluation protocols

to ensure accuracy, reproducibility, and fairness in benchmarking. You'll work closely with researchers and engineers to provide technical feedback that strengthens experimental rigor and system reliability.

You're a great fit if you:

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Have a background in

reinforcement learning, computer science, or applied AI research

. Are experienced with

RL environments

. Understand

benchmarking methodologies, terminal conditions, and evaluation metrics

for RL tasks. Are comfortable reading and reviewing codebases in

Python

(PyTorch/TensorFlow a plus). Have strong critical thinking skills and can provide

structured technical feedback

. Care deeply about

experimental reproducibility, fairness, and standardization

in agentic AI. Are detail-oriented and capable of reviewing both

theoretical formulations and implementation details

.

Primary Goal of This Role

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To review, validate, and improve reinforcement learning environment benchmarking pipelines, ensuring that terminal conditions, evaluation metrics, and system behaviors are robust, reproducible, and aligned with agentic AI research goals.

What You'll Do

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Review RL environments and

evaluate terminal conditions

for correctness and consistency. Assess

benchmarking pipelines

for fairness, reproducibility, and alignment with research objectives. Provide

structured technical feedback

on code implementations and documentation. Collaborate with researchers to refine

evaluation metrics and methodologies

. Ensure reproducibility by validating results across different

runs, seeds, and hardware setups

. Document findings and recommend improvements for

environment design and benchmarking standards

.

Why This Role Is Exciting

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You'll directly influence the

reliability of benchmarking in agentic AI research

. You'll work on

cutting-edge RL environments

that test the limits of intelligent agents. You'll help establish

standards for evaluation and reproducibility

in a fast-moving field. You'll collaborate with researchers shaping the

future of agentic AI systems

.
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract and Payment Terms

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You will be engaged as an independent contractor. This is a fully remote role that can be completed on your own schedule. Projects can be extended, shortened, or concluded early depending on needs and performance. Your work at will not involve access to confidential or proprietary information from any employer, client, or institution. * Payments are weekly on Stripe or Wise based on services rendered.