About the Company
Simile is The Simulation Company. We simulate human behavior to keep people at the center of the decisions that shape the world. With AI, anyone can create a product, a campaign, a policy, or a script — the bottleneck has moved upstream. The hard question is no longer whether you can create something, but what to create, for whom, and how to bring it to life. Those are fundamentally human decisions, and they shouldn't be left to chance or handed off to an algorithm. We're building the infrastructure to understand human behavior at scale and to represent humans in an increasingly agentic world. Our mission is to simulate all eight billion people on earth.
We launched five months ago. Since then we've grown revenue 5x, built a new foundation model for human behavior that has run tens of millions of simulations for F100 enterprises, trained a first-of-its-kind confidence model that predicts the accuracy of every simulation, and released the first product that lets organizations verifiably predict the future. The world's leading companies use Simile to make business-critical decisions — from consumer leaders like CVS Health and Wealthfront to professional services organizations like Deloitte and Gallup — strategizing product launches, entering new markets, and forecasting earnings calls.
We've raised over $200M at a $2B post-money valuation led by Greenoaks, with Index Ventures, Hanabi, A*, Bain Capital Ventures, and CVS Health Ventures. We've grown from a small home in Palo Alto to a global team of 50+, and we're building a team of the best researchers, engineers, designers, and operators in the world. The future is too important to be left to chance.
About the Role
As a Member of Technical Staff (MTS) in Research, you will work across the stack to train, evaluate, deploy, and monitor our models of human behavior. At Simile, we maintain a tight research-to-product pipeline. This requires intense scientific rigor; we must be able to trust our experimental methods as they are integrated into production systems that our customers use for making real high-stakes decisions.
We are looking for researchers who find it gratifying to see their work pushed to its absolute limits. You will own the research cycle end-to-end: from designing the initial experiments and validating results to owning the "last-mile" work of deployment.
In this role, you will:
Extract Insight from Unique Data: Work with massive, proprietary datasets that represent the breadth of human experience, including long-form unstructured interviews, large-scale polls, and passively collected behavioral data.
Master the Hardware: Write code for the latest NVIDIA chips. You will be responsible for running high-stakes experiments on GPUs and staying at the forefront of modern language model training and fine-tuning methodologies.
Lead Scientific Discovery: Design rigorous evaluations and conduct experiments that go beyond standard benchmarks to prove the fidelity of our behavioral simulations.
Push the State-of-the-Art: Stay immersed in the latest developments in simulation research. You will frequently reproduce, critique, and improve upon existing academic papers, maintaining a high standard for academic-quality writing and documentation.
Own the Lifecycle: Bridge the gap between a research hypothesis and a production-ready model, ensuring that our "flight simulators" for society are grounded in statistical truth.
Requirements
Must Haves
ML Proficiency: High proficiency in Python and hands-on experience with modern ML frameworks and AI coding tools.
Experimental Rigor: Experience running experiments on GPUs and a deep understanding of the training/fine-tuning lifecycle for large-scale models.
Research Literacy: Ability to navigate the frontier of ML research, with the technical skill to reproduce complex papers and the writing skill to document new breakthroughs.
End-to-End Ownership: A desire to own the full stack of research, from the first line of data processing code to the final deployment in a production environment.
Nice to Haves
Academic & Technical Foundation: An academic background in Computer Science, Math, Statistics, Deep Learning, Computational Social Science, or a related field.
Interdisciplinary Expertise: Experience in social science modeling or behavioral economics.
Large-Scale Systems: Familiarity with distributed training and optimizing inference for multi-agent environments.
Compensation & Benefits
At Simile, we provide competitive compensation packages that include base salary, equity, and comprehensive benefits.
Salary Range: $200,000 – $400,000 USD
Note: Final offers are based on experience, specialized skills, interview performance, and relevant training.
Equity: Grants are available for eligible roles, subject to board approval.
Health & Wellness: Comprehensive medical, dental, and vision coverage.
Time Off: Flexible time off policies to support work-life balance.
Our Process
We prioritize thoughtful conversations and clear examples of past work. Our hiring journey is designed to help both sides align on fit, working style, and expectations.
Reapplication Policy: To ensure a fair and thorough evaluation for all applicants, Simile observes a 90-day waiting period before reconsidering candidates for the same role.
Commitment to Diversity & Inclusion
Equal Opportunity: Simile is an equal opportunity workplace. We welcome applicants of all backgrounds and identities, valuing an environment where everyone can contribute authentically.
Accommodations: If you require support or reasonable accommodations during the application process due to a disability, please let us know. We are happy to assist.