Snorkel AI

HQ
Redwood
Year Founded: 2019

Snorkel AI Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers life insurance

Offers disability insurance

Offers supplemental life insurance

Offers childcare benefits

Offers generous parental leave

Offers company equity

Offers dental insurance

Offers health insurance

Offers mental health benefits

Offers dependent care

Offers Flexible Spending Account (FSA)

Offers vision insurance

Offers Health Savings Account (HSA)

Work-Life Balance + Wellbeing

Offers generous PTO

Provides paid holidays

Company Culture

Offers a remote work program

Recently posted jobs

2 Days AgoSaved
In-Office
2 Locations
Artificial Intelligence • Machine Learning
Leads Snorkel AI’s expert supply growth function, developing acquisition strategy, channel mix, partnerships, referral programs, BPO relationships, funnel optimization, analytics, and operating systems. Owns targets for acquiring, activating, and retaining specialized experts across domains and geographies. Builds and manages a high-performing team while partnering cross-functionally to improve quality, speed, cost, and marketplace capacity.
2 Days AgoSaved
Remote
United States
Artificial Intelligence • Machine Learning
Supports the payment lifecycle for expert contributors by managing payment support tickets, investigating discrepancies, resolving disputes, and communicating with contributors. Audits payment data and complex incentive structures, builds SQL queries, scripts, automations, and dashboards, and collaborates with Finance, Operations, Delivery, and Engineering. The role also supports payment compliance, data traceability, workflow improvements, and audit requirements.
5 Days AgoSaved
In-Office
San Francisco, CA, USA
Artificial Intelligence • Machine Learning
Build and scale machine learning systems for frontier AI data generation and evaluation. Responsibilities include efficient agentic evaluations, model routing, fine-tuning and serving smaller open-weight models, predictive task-difficulty modeling, LLM-as-judge measurement, and productionizing research prototypes. The role requires rigorous experimentation, statistical analysis, strong Python and software engineering, and end-to-end ownership of production ML or software systems.