Amigo
Research Scientist
– Amigo
About Amigo
Amigo builds AI agents for healthcare—systems that handle patient conversations, take clinical actions, and escale to humans when needed. Our agents operate autonomously within bounded clinical domains. We’re building the evaluation and safety infrastructure to validate agent performance at scale—simulation frameworks, outcome correlation, and systematic bias detection. Series A from leading investors. Clinical validation and evidence generation in partnership with leading academic medical institutions.
About This Role
As a Research Scientist at Amigo, you’ll lead our research agenda and publication strategy. You’ll design studies that validate AI agent performance, develop evaluation frameworks for clinical safety, and publish findings that set a new standard for healthcare AI research. This is a senior role focused on building Amigo’s research credibility through rigorous, reproducible work. We have an opportunity to lead the field—most healthcare AI research lacks publicly available datasets and rigorous methodology. You’ll change that.
What You’ll Do
Lead research on AI agent evaluation, simulation fidelity, and safety boundary testing
Publish preprints and peer‑reviewed papers at top venues
Design studies correlating agent interactions with clinical outcomes
Develop methods for detecting demographic biases in agent responses
Coordinate research collaborations with academic medical institutions
Ensure datasets are publicly available and methodologies are reproducible
Manage IRB processes and peer review submissions
Present findings at conferences and represent Amigo in the research community
What We’re Looking For
PhD in machine learning, statistics, computational healthcare, or related field from a top program
Strong publication record at top‑tier venues (NeurIPS, ICML, ICLR, AAAI, CHIL, etc.)
Experience with evaluation frameworks, benchmarking, or AI safety research
Track record of rigorous, reproducible research with public datasets
Ability to translate research findings into production improvements
Excellent written communication—clear, precise scientific writing
Experience coordinating with academic institutions
Nice to Have
Research experience at leading AI labs (industry or academic)
Publications on AI evaluation, safety, fairness, or healthcare ML
Experience with clinical study design or IRB processes
Background in simulation‑based evaluation or synthetic data
Track record of successful academic‑industry collaborations
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
Compensation Range:
$150,000 – $300,000
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Research, Analyst, and Information Technology
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– Amigo
About Amigo
Amigo builds AI agents for healthcare—systems that handle patient conversations, take clinical actions, and escale to humans when needed. Our agents operate autonomously within bounded clinical domains. We’re building the evaluation and safety infrastructure to validate agent performance at scale—simulation frameworks, outcome correlation, and systematic bias detection. Series A from leading investors. Clinical validation and evidence generation in partnership with leading academic medical institutions.
About This Role
As a Research Scientist at Amigo, you’ll lead our research agenda and publication strategy. You’ll design studies that validate AI agent performance, develop evaluation frameworks for clinical safety, and publish findings that set a new standard for healthcare AI research. This is a senior role focused on building Amigo’s research credibility through rigorous, reproducible work. We have an opportunity to lead the field—most healthcare AI research lacks publicly available datasets and rigorous methodology. You’ll change that.
What You’ll Do
Lead research on AI agent evaluation, simulation fidelity, and safety boundary testing
Publish preprints and peer‑reviewed papers at top venues
Design studies correlating agent interactions with clinical outcomes
Develop methods for detecting demographic biases in agent responses
Coordinate research collaborations with academic medical institutions
Ensure datasets are publicly available and methodologies are reproducible
Manage IRB processes and peer review submissions
Present findings at conferences and represent Amigo in the research community
What We’re Looking For
PhD in machine learning, statistics, computational healthcare, or related field from a top program
Strong publication record at top‑tier venues (NeurIPS, ICML, ICLR, AAAI, CHIL, etc.)
Experience with evaluation frameworks, benchmarking, or AI safety research
Track record of rigorous, reproducible research with public datasets
Ability to translate research findings into production improvements
Excellent written communication—clear, precise scientific writing
Experience coordinating with academic institutions
Nice to Have
Research experience at leading AI labs (industry or academic)
Publications on AI evaluation, safety, fairness, or healthcare ML
Experience with clinical study design or IRB processes
Background in simulation‑based evaluation or synthetic data
Track record of successful academic‑industry collaborations
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
Compensation Range:
$150,000 – $300,000
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Research, Analyst, and Information Technology
#J-18808-Ljbffr