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# Software Engineer - Dedicated Inference

- **Company:** Baseten, Inc
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Computer Programming, Databases, Software Debugging, Python (Programming Language), Web Applications, AI Infrastructure, Scripting, ReactJS, Kubernetes, Information Technology
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/software-engineer-dedicated-inference-baseten-6237876

## About the Role

* Bachelor's degree or higher in Computer Science or related field
 * Proficient coding abilities in one or more popular programming or scripting languages; Python, Go, or Javascript proficiency is a plus
 * Familiarity with web applications & databases
 * Good taste in product, particularly developer-oriented tools
 * Interest in ML/AI infrastructure and willingness to learn
 * Strong collaboration and communication skills

## Description

As a Product Engineer on the Dedicated Inference team, you'll shape the state-of-the-art developer experience for deploying and operating AI workloads in production. From the CLI and SDKs to APIs, observability, and debugging workflows, you'll build the tools customers rely on every day to manage mission-critical inference deployments.

Few teams at Baseten have as much breadth and visibility as Dedicated Inference. The team is often at the forefront of new product development, giving engineers the opportunity to shape the experience of some of our most important customers.

EXAMPLE INITIATIVES

You'll get to work on these types of projects as part of our Dedicated Inference team:

 * Chains for multi-component workflows
 * Asynchronous inference
 * Model APIs for frontier models
 * Model training built for production inference

RESPONSIBILITIES

 * Implement new features and products for the team
 * Design ergonomic APIs and abstractions to solve customer problems
 * Fix bugs and resolve customer issues with urgency
 * Work across the stack - regardless of where you start, you'll end up touching both React Components and Kubernetes Pods
 * Work closely with the product and forward deployed engineering teams to develop and drive new product ideas


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