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AmperosAI Research Engineer
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Before you apply
SalaryNo pay range posted
LocationNYC
Work modeon-site
Typefull-time
SenioritySenior
DepartmentEngineering
EquityIncluded
Company size51–200 people
PostedDec 19, 2024 · 1y ago
Verified live10h ago
May no longer be actively hiring
Posted by the company on Dec 19, 202471% of this company's open roles have been listed for 90+ daysNo pay range listed, though New York requires one
At a glanceSummarised by Seekless from the posting.
Deep experience in implementing and building AI agents
Worked with complex distributed systems with many async operations
Very high Python mastery
Excited about pushing the boundaries of conversational AI technology
Can balance quick experimentation with systematic evaluation
Eager to try out the latest releases (i.e. o1, OpenAI voice mode, Claude Computer-Use) to see how it can be used in real-world healthcare billing applications
You like reading the latest LLM research papers
Skills
Python
LLM
OpenAI
Claude
Benefits
Health insurance
Dental insurance
Vision insurance
401(k)
Gym stipend
Commuter benefits
Unlimited PTO
About Amperos
Amperos is healthcare’s first AI-native denial management and revenue recovery platform. Our agentic AI works claims end-to-end, from portal follow-ups and payor calls to appeals and medical records, so providers can resolve more denials, recover more revenue, and focus on what matters most: serving patients.
We just closed a $16M Series A led by Bessemer Venture Partners, with continued participation from Uncork Capital and Neo. We’re still small, still early, and going after a $260B+ problem that’s only getting worse. If you want to work on hard problems that matter, alongside people who care deeply about the mission (and each other), we’d love to meet you.
About the role
As an AI Engineer on our research team, you’ll work on our hardest research and AI infra problems. You’ll both help prototype new products and also work on turning prototypes into a high quality AI product. Hard problems include passing the healthcare billing Turing Test - would an insurance agent who is interacting with our AI or a healthcare biller who is reviewing the work of our AI think our AI is a human, and not an AI? More concretely, you will be working to improve our AI agent’s quality so it acts more human-like and collects more accurate and detailed results from insurance.
What you’ll do
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Main focus is on improving models, LLM orchestration, prompt optimizations, evaluation framework, and AI infra
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Enable agent/workflow product engineers
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Own and raise the bar on AI quality
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Own ultimate vision of end to end AI orchestration of modules
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Work on hardest research problems (ie. Anti-AI)
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Mainly a mix of ML, data science, and applied LLM work. Heavy Python.
Who we’re looking for
•
You like reading the latest LLM research papers
•
Deep experience in implementing and building AI agents
•
Eager to try out the latest releases (ie. o1, OpenAI voice mode, Claude Computer-Use) to see how it can be used in real-world healthcare billing applications
•
Worked with complex distributed systems with many async operations
•
Excited about pushing the boundaries of conversational AI technology
•
Can balance quick experimentation with systematic evaluation
•
Very high Python mastery
Perks & Benefits
•
In-person culture at our Flatiron office in NYC with paid lunch and dinner
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Flexible hours and time off
•
Gym stipend
•
Commuter benefits
•
Health, dental, vision insurance
•
401(k) with matching contribution
•
Annual offsite
Our Values
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Lead with Empathy - Great products and teams are built on empathy—whether for our customers, users, or team members. We take the time to walk in others’ shoes, listen actively, and truly understand their challenges, needs, and perspectives.
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Humbly Ambitious - We combine humility with ambition. No task is beneath us, and no challenge too big. Greatness comes from being willing to do whatever it takes, while having the courage to take bold risks and learn from failures.
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Radical Agency - Own your domain. Drive initiatives with autonomy and accountability. Think deeply, communicate with the team, and maintain a bias for action.