Distyl Inc. logo

Executive Assistant / Business Partner

Job Overview

Location

San Francisco

Job Type

Full-time

Category

Operations

Date Posted

April 9, 2026

Full Job Description

đź“‹ Description

  • • Executive Assistant / Business Partner role supporting the CEO at Distyl Inc., an applied AI technology company partnering with global enterprises to rearchitect critical operations using AI-native systems.
  • • Day-to-day responsibilities include managing and optimizing the CEO’s calendar, travel, and scheduling; serving as a trusted gatekeeper for the CEO’s time; driving preparation and follow-through for board and investor meetings; tracking company-wide initiatives; anticipating and resolving issues proactively; managing complex logistics across stakeholders; and creating systems to improve leadership team execution speed and clarity.
  • • Distyl is a fast-growing, mission-driven AI company backed by top-tier investors (Lightspeed, Khosla, Coatue, DST Global) with a 100% production deployment success rate and profitable business model, serving Fortune 500 clients across telecom, healthcare, insurance, manufacturing, and more.
  • • The role offers the opportunity to develop strategic influence, master executive-level operations in high-growth tech environments, build trusted relationships with investors and board members, and gain direct exposure to cutting-edge AI applications in enterprise settings while contributing to mission-critical workflows at scale.

Skills & Technologies

Hybrid
$160k-200k

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Distyl Inc. logo
Distyl Inc.
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About Distyl Inc.

Distyl is a cloud-native platform designed to simplify and accelerate the development and deployment of machine learning (ML) models. It provides a unified environment for data preparation, model training, versioning, and deployment, enabling data scientists and ML engineers to move from experimentation to production faster. The platform offers features such as automated data pipelines, managed training infrastructure, and scalable model serving. Distyl aims to reduce the complexity and operational overhead associated with MLOps, allowing organizations to focus on building and deploying impactful ML solutions. It supports various ML frameworks and integrates with existing cloud infrastructure.

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