FirstPrinciples - Senior Research Manager
Requirements
• A strong record of original research through publications, open-source systems, deployed methods, or comparable contributions. • Experience managing researchers or providing sustained technical leadership across ambitious programs. • A PhD or equivalent research experience in machine learning, computer science, physics, mathematics, scientific computing, or a related field. • Deep expertise in at least one relevant area, with the breadth to connect it to adjacent disciplines. • Strong programming and experimental skills, including the ability to engage deeply in implementation. • A record of moving research beyond demonstrations into validated, dependable, and reusable capabilities. • Excellent judgement about novelty, evidence, technical risk, and where to place long-term bets. • The ability to build trust and alignment across research, engineering, and scientific disciplines. • A low-ego, high-agency leadership style grounded in curiosity, precision, and intellectual honesty. • Relevant backgrounds may include scientific reasoning, reinforcement learning, post-training, agentic systems, automated conjecturing, theorem proving, world models, model merging, mechanistic interpretability, geometric deep learning, symbolic mathematics, AI for physics or mathematics, model architecture, scientific evaluation, physics-informed AI, differentiable simulation, or learned surrogate models. • Deep knowledge of physics or mathematics is especially valuable. We also welcome exceptional AI researchers motivated to develop that domain depth.
Responsibilities
• Define a research agenda spanning near-term capabilities, reusable platforms, and field-shaping bets. • Manage, mentor, and grow researchers with strong scientific taste, technical depth, and ownership. • Frame bold research theses and design decisive experiments, baselines, evaluations, and failure analyses. • Remain technically engaged in model development, post-training, data strategy, evaluation, and critical implementations. • Form integrated squads with engineering and domain experts from the outset of a program. • Help prototypes become reliable, reproducible, and reusable systems without losing their scientific insight. • Build compounding assets such as models, datasets, verifiers, benchmarks, simulations, agent runtimes, and research infrastructure. • Use evidence to decide when to deepen, redirect, scale, publish, protect, open-source, deploy, or conclude a line of work. • Influence broader research strategy, hiring, technical standards, infrastructure, and resource allocation. • RESEARCH QUESTIONS YOU MAY PURSUE • How can code execution, symbolic mathematics, theorem proving, and simulation provide scalable training and verification signals? • How can verifier-guided reinforcement learning and self-distillation improve long-horizon scientific reasoning? • How should scientific agents generate, test, revise, and preserve hypotheses across complex research programs? • What representations of mathematical functions and physical systems improve reasoning beyond text? • How can learned surrogate models and simulation-in-the-loop methods accelerate scientific discovery?
Benefits
• This is an opportunity to do more than manage a research team. You will help define a new research discipline, build the organization around it, and see the work become part of how science is actually done. • We support work across research horizons. Publications, open-source contributions, patents, reusable assets, decisive negative results, strategic learning, and deployed scientific capabilities are all meaningful forms of impact. • Great research here should teach us something important, make our systems more capable, create something others can build upon, or open a path that did not previously exist—ideally more than one. • Please submit a CV or resume and a brief statement describing: • A research direction that could materially advance AI-enabled scientific discovery. • A program you have led from initial hypothesis to evaluated results. • Your approach to technical leadership and multidisciplinary collaboration.
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