{"schemaVersion":"jobsearcher.job.v1","id":"ae36a3d6e77714e579c1fd68","url":"https://jobsearcher.com/jobs/ae36a3d6e77714e579c1fd68","canonicalUrl":"https://jobsearcher.com/jobs/ae36a3d6e77714e579c1fd68","title":"Machine Learning Engineer (Model Development)","description":"Kadence Talent is partnered with a pre-Series A healthtech AI company in the Bay Area, looking for a ML Engineer (Data Scientist, model development)Machine Learning Engineer, Model DevelopmentAbout the RoleMedical coding is a high-stakes domain: a model error isn't just an incorrect prediction — it can become a billing, compliance, revenue, or trust issue. We're looking for someone who can improve model quality systematically, combining strong ML engineering, evaluation design, prompt engineering, and domain learning.We're hiring an ML Engineer to build and improve specialty-specific medical coding agents. You'll work closely with engineering, clinical coding experts, auditors, and customers to turn model failures into measurable improvements.This is a hands-on role at the intersection of applied machine learning, LLM-based agent development, evaluation systems, and healthcare data workflows. You'll own the feedback loop that takes audited coding decisions, clinical edge cases, and production failures — and turns them into better agents.What You'll DoBuild & Improve AI Coding AgentsBuild, maintain, and iterate on specialty-specific coding agents. Translate expert and auditor feedback into concrete improvements. Run structured improvement cycles — batched feedback, test sets, regression checks — rather than one-off fixes.Design Evaluation SystemsBuild evaluation harnesses and gold-standard datasets. Create regression tests so changes don't silently break existing behavior. Build confidence scoring and metrics that are meaningful to both engineers and clinicians.Write & Iterate Prompts and Agent LogicDesign prompts for clinical evidence extraction, coding recommendations, and rationale generation. Build and improve agent scaffolding — prompt chains, tool use, evaluation loops. Work toward model-agnostic evaluation across foundation models.Work With Clinical CodersPartner directly with certified medical coders to understand coding rules and edge cases. Convert their feedback into precise engineering tasks. Help non-technical stakeholders understand model behavior and tradeoffs.What We're Looking For2+ years building applied ML, LLM-based systems, or AI agents in productionStrong Python skills and comfort with messy, real-world dataExperience building evaluation frameworks, benchmarks, or quality-measurement systemsSolid statistical reasoning — precision/recall, confidence intervals, error analysisHands-on experience with LLMs, prompt engineering, or agentic systemsAbility to debug model failures by reading examples closely and designing structured fixesComfort with early-stage ambiguity and fast iterationNice to HaveHealthcare, claims, or clinical NLP experience; familiarity with CPT/ICD-10/payer rules; human-in-the-loop ML systems; document AI/OCR; Claude/OpenAI API experience; HIPAA/SOC 2 exposure.Location: Bay Area, CAComp: $140k-180k, plus equity.","company":"Kadence","rawCompany":"kadence","city":"Menlo Park","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-15T09:19:44.204Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer (Model Development)","description":"Kadence Talent is partnered with a pre-Series A healthtech AI company in the Bay Area, looking for a ML Engineer (Data Scientist, model development)Machine Learning Engineer, Model DevelopmentAbout the RoleMedical coding is a high-stakes domain: a model error isn't just an incorrect prediction — it can become a billing, compliance, revenue, or trust issue. We're looking for someone who can improve model quality systematically, combining strong ML engineering, evaluation design, prompt engineering, and domain learning.We're hiring an ML Engineer to build and improve specialty-specific medical coding agents. You'll work closely with engineering, clinical coding experts, auditors, and customers to turn model failures into measurable improvements.This is a hands-on role at the intersection of applied machine learning, LLM-based agent development, evaluation systems, and healthcare data workflows. You'll own the feedback loop that takes audited coding decisions, clinical edge cases, and production failures — and turns them into better agents.What You'll DoBuild & Improve AI Coding AgentsBuild, maintain, and iterate on specialty-specific coding agents. Translate expert and auditor feedback into concrete improvements. Run structured improvement cycles — batched feedback, test sets, regression checks — rather than one-off fixes.Design Evaluation SystemsBuild evaluation harnesses and gold-standard datasets. Create regression tests so changes don't silently break existing behavior. Build confidence scoring and metrics that are meaningful to both engineers and clinicians.Write & Iterate Prompts and Agent LogicDesign prompts for clinical evidence extraction, coding recommendations, and rationale generation. Build and improve agent scaffolding — prompt chains, tool use, evaluation loops. Work toward model-agnostic evaluation across foundation models.Work With Clinical CodersPartner directly with certified medical coders to understand coding rules and edge cases. Convert their feedback into precise engineering tasks. Help non-technical stakeholders understand model behavior and tradeoffs.What We're Looking For2+ years building applied ML, LLM-based systems, or AI agents in productionStrong Python skills and comfort with messy, real-world dataExperience building evaluation frameworks, benchmarks, or quality-measurement systemsSolid statistical reasoning — precision/recall, confidence intervals, error analysisHands-on experience with LLMs, prompt engineering, or agentic systemsAbility to debug model failures by reading examples closely and designing structured fixesComfort with early-stage ambiguity and fast iterationNice to HaveHealthcare, claims, or clinical NLP experience; familiarity with CPT/ICD-10/payer rules; human-in-the-loop ML systems; document AI/OCR; Claude/OpenAI API experience; HIPAA/SOC 2 exposure.Location: Bay Area, CAComp: $140k-180k, plus equity.","datePosted":"2026-07-15T09:19:44.204Z","dateModified":"2026-07-15T09:19:44.204Z","hiringOrganization":{"@type":"Organization","name":"Kadence","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ae36a3d6e77714e579c1fd68"},"url":"https://jobsearcher.com/jobs/ae36a3d6e77714e579c1fd68"}}