# Staff ML Engineer, AI Platform

**Company:** [Ambience Healthcare](https://hotfix.jobs/companies/ambience-healthcare)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $250k – $300k/yr
**Experience:** 7+ years
**Skills:** Python, TypeScript, ML Infrastructure, MLOps, Data Pipelines, Eval Systems, Observability, Kubernetes, Retrieval Systems, Model Serving
**Posted:** 2026-02-02

> Builds ML platform infrastructure including evaluation/release gates, debug tooling, chart context retrieval, data pipelines, and model serving to accelerate AI improvements for clinical workflows. Requires 7+ years software engineering with 3+ in ML infra/platform, strong Python/TypeScript backend skills.

## Job Description

## What You’ll Own

**Eval & Release Infrastructure**
- Automated graders and release gates that work across product pods
- Unified eval dataset versioning and execution to replace fragmented workflows
- Production quality monitoring with end-to-end tracing, shared metrics, and automated alerting

**Debug Tooling**
- Encounter replay that reconstructs exact inference inputs (retrieved chart context, packed prompts, model versions) so teams reproduce issues without digging through logs
- Diff views comparing known-good runs to regressions

**Chart Context & Data Pipelines**
- The retrieval layer that pulls relevant patient history and assembles it into consistent model-ready inputs
- Feedback loops that capture real-world usage and convert it into training signal
- End-to-end latency instrumentation across every workflow step

**Preference Infrastructure**
- The system that enables clinician and site-specific behavior across specialties
- Different clinics want different defaults, different phrasing, different workflows. Build the platform that supports customization at scale

**Model Serving**
- Performance and reliability layer for critical in-house models with clear SLOs, capacity planning, and regression alerts

## Who You Are

- 7+ years in software engineering, 3+ focused on ML infrastructure, platform engineering, or data systems
- Staff-level scope: owned cross-cutting infrastructure, influenced technical direction across multiple teams
- Strong backend fundamentals in **Python**, **TypeScript**, or similar
- Built eval systems, data pipelines, or ML observability infrastructure
- Comfortable on both the ML and Eng sides of MLOps
- Track record of platform work that measurably accelerated other teams
- In SF, 3x/week in-person

## Compensation

Base compensation range of approximately **$250,000-300,000** per year, exclusive of equity.

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**Apply:** https://hotfix.jobs/jobs/6b870334-8fcd-4d68-8fe1-de7b1e960ae5
**Canonical:** https://hotfix.jobs/jobs/6b870334-8fcd-4d68-8fe1-de7b1e960ae5