Model Pragmatism Jobs in San Francisco, CA

Write effective Python and SQL and can investigate imperfect data, debug models, and make pragmatic implementation choices.

Design and improve Harvey's Unified Model Controller (UMC) and Model Selector platform to automatically detect model degradations and intelligently

, or similar Compared modeling approaches and made pragmatic decisions about when to use traditional ML, LLMs, heuristics, or simpler baselines

Comfort working across model behavior, context, knowledge, tools, workflow state, and human-in-the-loop decisions.

Strong sense of ownership and bias for action: you own outcomes, not tasks; you move fast, make pragmatic decisions, and thrive in ambiguity

You're well-versed in data modeling best practices (dimensional modeling, star/snowflake schemas, slowly changing dimensions) and know how to optimize

These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads.

integral role in building our culture as the company grows and mentor other engineers as we scale the team You will balance innovation with pragmatic

Build generative UIs that let users create real apps from natural language Improve the performance, observability, and safety of our internal model

You’ve deployed classifiers or machine learning models, or are excited to learn about modern ML infra.

Bias for speed and pragmatism: you default to "how do I get this out the door as fast and sharply as possible," not "how do I make this perfect."

Experience deploying models through APIs or real-time decision systems.

A pragmatic, product-minded approach.