Research Engineer (Simulation Systems)

Reposted 2 Days Ago
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San Francisco, CA
In-Office
150K-300K Annually
Mid level
Artificial Intelligence • Enterprise Web • Healthtech • Software
Building healthcare AI systems organizations stake their reputations on—trust & safety infrastructure for clinical agent
The Role
As a Research Engineer, you will develop high-fidelity simulation systems for AI in healthcare, ensuring reliability and accuracy in decision-making through modeling and real-world data validation.
Summary Generated by Built In
About Amigo

Amigo builds trust and safety infrastructure for AI in mission-critical environments.

We partner with organizations in healthcare and other regulated sectors to deploy AI systems that operate reliably when the stakes are highest. Our infrastructure enables verification, monitoring, and real-time oversight—ensuring AI serves people safely at scale.

We've raised $6.5M from General Catalyst and GSV Ventures. Our team combines expertise in distributed systems, quantitative research, clinical operations, and regulatory environments to build AI that organizations can trust.

About this role

As a Simulation Systems Research Engineer at Amigo, you'll build the high-fidelity simulation infrastructure that enables our AI systems to provide statistical confidence in healthcare decisions. You'll design and implement systems that model complex healthcare environments, patient interactions, and deployment contexts under compute constraints. Your work directly enables the translation of simulated performance to real-world outcomes, forming the foundation of our approach to reliable AI in critical domains.

What you'll do
  • Build high-fidelity simulation systems that model healthcare environments and patient interactions

  • Create systems that simulate real-world edge cases: network failures, background noise, system crashes

  • Develop frameworks for testing AI behavior across diverse patient populations

  • Build tools for validating simulation accuracy against real-world healthcare data

  • Design distributed systems that can scale to millions of test scenarios

  • Collaborate with healthcare experts to ensure simulations capture critical clinical details

What we're looking for
  • Experience building complex simulation systems

  • Strong background in distributed systems and high-performance computing

  • Experience with simulation frameworks and modeling complex real-world systems

  • Knowledge of statistical sampling and Monte Carlo methods

  • Track record of building production systems that handle large-scale data processing

Nice to have
  • Healthcare industry experience or familiarity with clinical environments

  • Experience with high-throughput computation and distributed processing systems

  • Background in computational modeling or scientific computing

  • Knowledge of privacy-preserving techniques for healthcare data

Benefits

Health & Wellness
  • Comprehensive health, dental, and vision insurance

  • Mental health support and wellness coaching

  • Flexible wellness stipend for fitness, therapy, or personal growth

  • Daily catered lunch and dinner

Growth & Development
  • Annual learning budget for courses, books, or conferences

  • Conference attendance budget for professional development

  • Development setup of your choice

  • Academic collaboration opportunities

Top Skills

Distributed Systems
High-Performance Computing
Monte Carlo Methods
Simulation Frameworks
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The Company
HQ: New York, New York
15 Employees
Year Founded: 2024

What We Do

Amigo AI builds trust and safety infrastructure for clinical agents—ensuring AI systems in healthcare provide quantified confidence when mistakes aren't an option. Our platform combines advanced simulation, verification, and recursive optimization to enable healthcare organizations to deploy AI with statistical guarantees about its behavior.

We solve the fundamental challenge of reliable AI in critical domains through deterministic verification for clinical protocols and continuous drift detection for real-world performance. Our systems provide complete transparency—every AI decision is traceable and auditable, with quantified confidence intervals rather than black box predictions.

Founded by technologists from Google, Meta AI, Databricks, Coda, and Plaid, we've built systems that let organizations make informed risk decisions about AI deployment in healthcare. Our interdisciplinary approach draws from computer science, economics, physics, and mathematics to tackle human-centric optimization problems where people and populations are at the center of every solution.

We're actively working with healthcare organizations across digital health, cancer care, cardiac care, and personalized medicine to deploy AI systems that continuously learn and adapt from real-world feedback while maintaining verified safety boundaries. Our technology amplifies human expertise rather than replacing it, empowering domain experts to achieve outcomes neither could accomplish alone.

Why Work With Us

We build AI healthcare systems where 99% isn't good enough. Rapid growth—promotions in 3 months. Freedom to work your way: art museums or late nights. Tackle recursive optimization problems that ship to production. Your work directly impacts critical healthcare decisions. Diverse team from Google, Meta AI, Databricks solving problems that matter.

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