Drift Model Jobs in San Francisco, CA

In this role, you will take a failure from a log to an assigned root cause, owning the triage classification, the severity model, and the diagnostic tooling that

A lightweight, model-agnostic system that enforces policy, prevents drift, and produces auditable decisions in real time.

We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products

and modern transformer architectures Developing monitoring and alerting systems for ML model performance and data drift Experience in trust &

(e.g., in-memory S2 grids), and continuous model drift monitoring.

Familiarity with the operational realities of multi-tenant model serving (LoRA/adapter-based serving) and with running differentiated SLOs across model

, models, and product.

A lightweight, model-agnostic system that enforces policy, prevents drift, and produces auditable decisions in real time.

Monitor models in production: feature drift, score distribution shifts, and model versus random arm results.

Familiarity with the operational realities of multi-tenant model serving (LoRA/adapter-based serving) and with running differentiated SLOs across model

This is not a purely operational role — your research directly drives features, model inputs, and product design.

Standing up our ML infrastructure: training and inference pipelines, experiment tracking, model versioning, and evals - so that every model we ship is

simulation, managing training data, evaluating models, and deploying optimized models to edge systems.

for sensor arrays: excitation, lock-in/demodulation, ADC selection, noise budgeting Develop and validate signal processing and calibration algorithms (drift