Research Program Manager - Model Data & Evaluations Flywheel

Reflection AI Ltd

New York (NY)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Benefits offered by this job

Top-tier compensation
Stock options
Health & wellness
Meals provided
Parental leave
Unlimited PTO
Visa sponsorship
Team off-sites

Job summary

Reflection invites a Research Program Manager to join as a foundational, zero-to-one function creator for model safety and evaluation. You will define evaluation frameworks, build operational infrastructure for safety, and connect evals to the model development lifecycle.

You’ll work with researchers and engineers to ensure rigorous yet nimble processes that scale with rapid AI progress. You will lead cross-functional collaboration, establish workflows and cadence, and drive risk-informed

Qualifications

  • 7+ years in technical program management, research operations, or ML engineering.
  • Familiar with model evaluation and AI safety, including evaluation methodologies and red-teaming.
  • Deep technical ability to engage with researchers and engineers on model behavior and data pipelines.

Responsibilities

  • Define evaluation frameworks and tooling for model evals and safety.
  • Stand up model safety operations with workflows and decision frameworks.
  • Embed safety checkpoints across pre-training to post-training workflows.
  • Prioritize eval science and infrastructure investments with technical leads.
  • Engage with external safety ecosystem and represent safety posture externally.
  • Create visibility and reporting structures for leadership on safety status.

Skills

Technical program mgmt
Research operations
ML engineering
Stakeholder mgmt
Problem solving

Tools

Model evals

Job description

Our Mission

Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.

About the Role

Research Program Managers at Reflection are high-leverage leaders and operators who embed directly with research and infrastructure teams to accelerate the pace of frontier model development. They are not project trackers. They are force multipliers who bring clarity to ambiguity, drive decisions when the path forward is unclear, and ensure that the work happening across multiple teams connects into a coherent whole.

This is a foundational role. Reflection is building model evals and safety from the ground up, and this RPM will be at the center of that effort. You won't be stepping into an established function with existing processes and tooling. You will be the person who figures out what this function needs to look like, stands it up, and makes it real. That means defining the evaluation frameworks, building the operational infrastructure for model safety, establishing the processes that connect evals to the model development lifecycle, and laying the groundwork for how Reflection interfaces with the broader safety ecosystem. This is 0-to-1 work in its purest form.

You bring a first-responder mentality. When things go sideways, you don't wait to be asked. You jump in, assess the situation, cut through noise, align the people who need to be aligned, and drive resolution.

What You'll Do
  • Build the foundational infrastructure for model evals and safety at Reflection. Define the evaluation frameworks, tooling requirements, and operational processes that will underpin how we assess model capabilities, risks, and readiness for release.

  • Stand up model safety operations as a function, including establishing the workflows, review cadences, and decision frameworks that connect safety evaluation to the model development and release lifecycle.

  • Partner with research and engineering leads across pre-training, mid-training, and post-training to embed safety and evaluation checkpoints into the development process in a way that is rigorous without being a bottleneck.

  • Drive the scoping and prioritization of eval science and eval infrastructure investments, working with technical leads to determine what to build in-house, what to adopt, and where to invest research effort.

  • Establish Reflection's engagement with the external safety ecosystem, including third-party assessments, academic partnerships, and industry safety frameworks. Represent the company's safety posture to external stakeholders with credibility and clarity.

  • Create visibility and reporting structures that give leadership a clear, honest picture of model safety status, evaluation coverage, and open risks, so they can make informed decisions at the pace the business requires.

  • Champion a culture of blameless post-mortems and continuous learning, turning every safety-relevant finding into a concrete improvement to our systems and processes.

About You
  • 7+ years of experience in technical program management, research operations, or ML engineering, with demonstrated experience standing up new functions, teams, or programs from scratch.

  • Familiar with the landscape of model evaluation and AI safety, including evaluation methodologies, red-teaming, alignment research, and the evolving regulatory and industry safety ecosystem. You don't need to be a safety researcher, but you need to understand the space well enough to make sound judgments about what matters and what to prioritize.

  • Deep enough technically to engage with researchers and engineers on topics like model behavior, evaluation design, data pipelines, and safety-critical system architecture. You follow the technical thread and you know when something doesn't add up.

  • Proven ability to build structures where none exists. You've taken ambiguous mandates and turned them into functioning programs with clear ownership, measurable outcomes, and durable processes.

  • Strong stakeholder management skills spanning deeply technical ICs, research leadership, and external partners. You build trust through competence and follow-through.

  • Excited to build from zero to one. We are a small, fast-moving team and this role will help define how model safety and evaluation works at Reflection.

  • Motivated by enabling researchers and engineers to build the world's most capable open-weight AI systems, responsibly.

What We Offer:

We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models.

We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.

  • Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.

  • Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.

  • Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.

  • Meals: Lunch and dinner are provided in the office daily.

  • Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.

  • Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.

  • Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.

  • Team building: We have regular off-sites, happy hours, and team celebrations.

Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization.

Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice

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