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NEXTMOVEFDE careers · United States

Simulation Engineer

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

Technologies

Large Language Models · deep learning · probabilistic modeling · Bayesian inference · causal reasoning · multi-agent systems · NeurIPS · ICML · ICLR · ACL

About Aaru

Builds an agentic prediction engine that spins up thousands of AI agents to forecast human behavior (elections, markets, opinion) for enterprise and campaign clients.

Series A · 20–50 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Internal deployment & tooling · Evidence for this classification:

space to operate without bureaucratic friction. We work with urgency and intellectual honesty and expect new team members to match our velocity. We seek individuals who thrive at the frontier, who push beyond conventional limits, who bring curiosity and conviction in equal measure, and who want their work to have demonstrable impact in the world. If you're energized by the idea of a small team doing things that feel impossible, let’s build together. ABOUT THE ROLE Simulation Engineering owns the path from research idea to production system. Researchers prove out how to synthesize an audience, model a world, predict responses, score accuracy, or ship a result; you turn those ideas into robust, reusable, fast code — the objects, contracts, evaluations, and workflows that produce the product. RESPONSIBILITIES Productionize the core simulation loop — audience generation, world modeling,
More from the job description

ABOUT AARU Aaru operates at the frontier of predictive intelligence, using AI to simulate and predict human behavior at scale. By generating and deploying instances of artificial intelligence that mirror humans, called agents, Aaru simulates entire populations with unprecedented accuracy. Our partners use Aaru to refine strategic positioning, identify and understand high-value audiences, validate concepts and messaging before launch, optimize pricing decisions, and build a continuously richer understanding of their customers through simulation. We provide organizations with invaluable foresight, empowering them to anticipate outcomes and proactively make the right decisions at the right time, every time. We're a small, dedicated, mission-driven team and we intend to stay that way. We believe the best work happens when exceptionally talented people are given ownership, trust and the space to operate without bureaucratic friction. We work with urgency and intellectual honesty and expect new team members to match our velocity. We seek individuals who thrive at the frontier, who push beyond conventional limits, who bring curiosity and conviction in equal measure, and who want their work to have demonstrable impact in the world. If you're energized by the idea of a small team doing things that feel impossible, let’s build together. ABOUT THE ROLE Simulation Engineering owns the [... source excerpt omitted ...] responses, score accuracy, or ship a result; you turn those ideas into robust, reusable, fast code — the objects, contracts, evaluations, and workflows that produce the product. RESPONSIBILITIES Productionize the core simulation loop — audience generation, world modeling, response prediction. Design the reusable abstractions that the product is made of: agent and population objects, simulation contracts and interfaces, evaluation harnesses, etc. Build and own evaluation and accuracy infrastructure. Make simulations fast and cheap enough to run at scale. Partner closely with Simulation Research to harden hybrid LLM + classical architectures. Build the workflows and tooling that [... source excerpt omitted ...] and forward-deployed teams stand up new client simulations. Create the calculation, analysis, and publication layers that turn raw agent output into the decision-ready artifacts customers see. Hold the line on engineering quality across a fast-moving codebase. YOU MAY BE A FIT IF You have deep expertise in ML and AI, with meaningful prior work using Large Language Models in production systems You've designed and run rigorous ML experiments, moving from hypothesis to evaluation to deployment You have 3+ years of hands-on experience building ML/AI systems (research or applied) You're comfortable working across the full model lifecycle: data collection, training, evaluation,

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