River AI · Data and evaluation profile

Collect the data that makes behavior measurable.

Mohamed A M Elansary, PhD — multi-model evaluation, uncertainty quantification, scientific data/HPC pipelines, and production agent regression evaluation.

Data evaluation workflowsModel behaviorUncertainty quantificationScientific HPC

Evaluation discipline

  • Designed multi-model forecast comparisons across basins and hydroclimates.
  • Validated imperfect observations before interpreting model performance.
  • Reported uncertainty and regime-dependent failures instead of one score.

Production agent systems

  • Builds GPT, Claude, and Gemini workflows at Vertexium.
  • Maintains regression evaluation sets for retrieval, routing, and isolation behavior.
  • Connects data, validation, provenance, and reporting in Python pipelines.

Proposed first contribution

Choose one user-visible agent behavior; define the slices and failure taxonomy; version an evaluation set with provenance; compare simple baselines; report uncertainty; then identify the next data worth collecting before scaling the campaign.

Honest fit boundary

Operational human-labeling management is a major minimum and a substantial stretch. I have supervised research staff, junior engineers, engineers, and contractors, but I have not hired or managed human data labelers or operated external labeling campaigns. I have not run frontier-lab post-training, RLHF, or RL/SFT recipes.

Role and location

Member of Program Staff, Data · Palo Alto, CA. I am willing to relocate with a relocation package and do not assume remote eligibility.

“expected base pay is $200,000 - $300,000 USD per year” · Official role posting