Remote Drift Model Jobs

Review ongoing monitoring plans and results, including performance thresholds, overrides, data drift, model changes, and conditions that could make a model

Able to read a model and interrogate its methodology: performance evaluation, calibration, drift, backtesting, and fairness.

Track how each project is performing against its targets, diagnose what is drifting, and act before it reaches the client.

But you also understand what breaks for a customer when a pipeline is late, a metric drifts, or a model gets stale data.

for clients hosting their own Own models in production: monitoring, drift detection, retraining, incident response, and the on-call rotation

Document platform standards, operational expectations, and support models so the Databricks platform can scale beyond a small founding team.

Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data.

Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data.

We are also aiming to solve Design <> Code parity and minimize drift away from the defined design system in both code and designs.

building observability and alerting for production services: latency, errors, and ideally model-specific signals like drift Comfort with the data layer

Learn how model performance is monitored in production, including data quality, drift, and operational reliability.

But you also understand what breaks for a customer when a pipeline is late, a metric drifts, or a model gets stale data.

At the center is Albus, our AI agent for identity — mining roles, approving access, and catching the drift humans miss.

Test system prompts, context retrieval, and model selection to boost output quality, seller adoption, and deal velocity.

Deep expertise in transformer-based models, embeddings, retrieval systems, and Retrieval-Augmented Generation (RAG) pipelines.