Job Overview
Location
San Francisco
Job Type
Full-time
Category
Software Engineering
Date Posted
May 8, 2026
Full Job Description
📋 Description
- • AI Engineer role focused on building and operating production AI systems that deliver real business value for enterprise customers in telecom, healthcare, insurance, manufacturing, and more
- • Design, deploy, and iterate on end-to-end AI workflows combining models, agents, retrieval, evaluation, and execution while working closely with customer stakeholders to translate requirements into reliable systems
- • Distyl is an applied AI technology company backed by top investors, partnering with Fortune 500 institutions to rearchitect critical operations using self-constructing AI systems with a 100% production deployment success rate
- • Opportunity to own high-impact AI systems, develop deep expertise in AI-native engineering practices, and grow technically by working on real-world problems at scale with access to state-of-the-art models and tools
🏖️ Benefits
- • Base salary range of $150K – $250K depending on experience, location, and level
- • 100% covered medical, dental, and vision for employees and dependents
- • 401(k) with additional perks including commuter benefits and in-office lunch
- • Access to state-of-the-art models and generous usage of modern AI tools
- • Ownership of high-impact projects across top enterprises
- • Mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence
Skills & Technologies
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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