Full-Time

Special Projects Operator

Idler

Idler

AI agents automate back-office workflows

Compensation Overview

$140k - $250k/yr

+ Equity

San Francisco, CA, USA

In Person

Relocation assistance is available.

Category
Business & Strategy (1)
Required Skills
Product Management
Quality Assurance (QA)

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Requirements
  • Ability to take high ownership and proactively fix problems.
  • Ability to turn ambiguity into structured plans and measurable outcomes.
  • Ability to maintain a high standard for correctness and follow-through.
  • Ability to perform effectively in fast-moving environments with shifting constraints.
  • Interest in responsibility tied directly to output and business impact.
Responsibilities
  • Own execution of multi-million-dollar programs from scope through delivery.
  • Orchestrate hundreds to thousands of expert contributors under aggressive timelines.
  • Design and iterate on workflows, incentive systems, and quality controls to improve throughput, margins, and reliability.
  • Run quality assurance reviews, surface delivery risks early, and remove bottlenecks before they escalate.
  • Track throughput, quality, cost, and timeliness, and translate performance into clear updates for leadership.
  • Partner with senior stakeholders to align on scope, iterate quickly, and expand engagements through strong execution.
Desired Qualifications
  • Experience running large distributed teams or marketplaces.
  • Background in consulting, finance, high-growth startups, or product or operations roles with end-to-end accountability.

Idler provides AI agents that automate back-office and operational tasks for businesses. Its platform combines document parsing, decision logic, and agent-driven execution to manage end-to-end workflows such as order fulfillment, payment collection, and service scheduling, including PO processing and invoicing. It configures automations that update trackers, send emails, and coordinate with vendors and clients, with human intervention only when needed. It starts with a four-week pilot to map workflows, set up and tune automations, and measure impact, followed by a tailored plan to scale. The goal is to reduce manual work and boost efficiency for organizations that rely heavily on spreadsheets, emails, and vendor portals.

Company Size

N/A

Company Stage

Seed

Total Funding

$9.1M

Headquarters

San Francisco, California

Founded

2025

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Simplify Jobs

Simplify's Take

What believers are saying

  • Idler raised $9M on August 19, 2026, extending runway.
  • Idler claims an unnamed frontier lab saw eightfold long-horizon coding gains.
  • YC now invites 10-to-100 employee firms to license data, widening supply.

What critics are saying

  • Idler named no customers, so buyers can demand proofs before paying.
  • Grading systems can reward their own benchmarks, creating integrity risk inside 2026.
  • OpenAI, Anthropic, and in-house lab teams can internalize evals by 2027.

What makes Idler unique

  • Idler builds frontier-model evals and RL environments, not generic enterprise software.
  • It sources realistic tasks from real codebases and de-identified business data.
  • YC Summer 2025 and Paradigm-backed capital give it elite AI-lab access.

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Benefits

Health Insurance

Meal Benefits

Relocation Assistance

Paid Vacation

Company Social Events

Company News

The Adventurer
Aug 20th, 2026
idler raises $9M led by Paradigm to sell evals and RL environments to frontier AI labs

idler launched on 19 August as a frontier data research lab with a $9 million seed round led by Paradigm, alongside Y Combinator, Long Journey VC and angels. The company sells evaluations, benchmarks and reinforcement learning environments to labs training frontier models. The timing suggests a real market. Z.ai described synthesizing RL environments end to end for GLM-5.3, and Harvey built LAB environments before post-training Tenet — both announcements made the same week. Paradigm's involvement marks a notable rotation of crypto capital into AI infrastructure. The business model targets perhaps 15 organisations worldwide, making it high-margin but low-volume. The announcement contains no product details, methodology or named customers. For a company whose credibility depends on client names, this absence is significant. The company also does not address the independence question raised by grading systems its own customers are measured against.