Research Program Manager

Reinforced Learning; Town of Tonawanda (NY); Sur place; USD 90 000 - 130 000; Plein temps

Résumé du poste

Reinforced Learning is seeking a Research Program Manager to run the operations behind its research programs, including benchmark releases, collaborations with academic and industry partners, and the research roadmap.

You will coordinate external relationships, track progress, read results tables, and translate research needs into engineering and operational plans, while communicating clearly with researchers and executives.

Qualifications

• 1–3+ years in research operations or tech program management.
• Technical background in CS/ML/stats with Python and SQL.
• Ability to read results tables and trust evaluation numbers.
• Excellent written and verbal communication for partner and exec audiences.
• Experience running cross-functional programs end to end with external partners.

Responsabilités

• Coordinate collaborations with academic and industry partners from scoping to delivery.
• Manage end-to-end benchmark releases, from launch to publication.
• Maintain leaderboards and verify results before publication.
• Track progress, identify bottlenecks, and adjust timelines.
• Coordinate expert pool for upcoming benchmarks and logistics.
• Write launch briefs, partner updates, and status memos.

Connaissances

Research ops

Tech program mgmt

Python

SQL

Communication

Cross-functional programs

Ambiguity handling

Formation

Graduate degree in technical field

Description du poste

Reinforced Learning is hiring a Research Program Manager to run the operations behind its research programs: public benchmark releases, collaborations with academic and industry partners, and the research roadmap. You own the coordination, external relationships, and progress tracking that keep the program moving, and you are welcome to contribute to the research itself, from benchmark design to co-authoring publications.

Overview

Reinforced Learning is hiring a Research Program Manager to run the operations behind its research programs: public benchmark releases, collaborations with academic and industry partners, and the research roadmap. You own the coordination, external relationships, and progress tracking that keep the program moving, and you are welcome to contribute to the research itself, from benchmark design to co-authoring publications.

This is a technical, hands‑on role, not a pure coordination one. You will read results tables, run evals, sanity‑check numbers before they go public, and turn loosely specified research needs into engineering and operational roadmaps. You will also be the program's voice to external partners, so clear writing and confident communication across researchers, executives, and academics are as important as technical fluency. You work daily with researchers, engineers, domain experts, and go‑to‑market partners.

Responsibilities

• Serve as the point of contact for collaborations with academic and industry partners, including fellowships, grants, and joint research projects, and run each from scoping through delivery.
• Coordinate benchmark releases end to end, from launch checklist through publication, and keep releases on cadence.
• Maintain Reinforced Learning's leaderboards and benchmark sites, and verify every result before it goes to a community leaderboard or publication.
• Track progress across all active research projects. Anticipate resourcing gaps and technical bottlenecks, unblock projects that fall behind, and elevate with a clear recommendation when a timeline or scope needs to change.
• Coordinate the expert pool for upcoming benchmarks: forecast expert needs, manage capacity, and keep contributor logistics running.
• Write the program's external and internal communications: launch briefs, partner updates, planning documents, and status memos that turn technical detail into clear, actionable summaries.

Required Qualifications

• 1-3+ years in research operations, technical program management, or a similar role in a fast-moving research or engineering organization.
• Technical background in computer science, machine learning, statistics, or a related field, with working Python and SQL.
• Evaluation literacy: you have taken part in evaluating a product, an agent, or a foundation model, can read a results table, and can tell when a number should not be trusted.
• Excellent written and verbal communication. You can distill a technical result into a summary a partner, executive, or academic collaborator can act on, and you write documents people actually read.
• A track record of running cross-functional programs end to end, including managing external partners, contractors, or collaborators.
• Comfort with ambiguity and building processes from scratch, and the judgment to keep processes light so researchers stay effective.

Preferred Qualifications

• Graduate degree or research experience in a technical field.
• Contributed to a benchmark, dataset, or evaluation project in any role.
• Familiarity with public leaderboards or open research communities.
• Exposure to programs with external partners, such as fellowships, grants, or academic collaborations.
• Exposure to expert or annotator pools, or other human-data work.
• Comfort with lightweight dashboards or building small tools with AI assistants.