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# Software Engineer, Bulk/Interactive Inference

- **Company:** Waymo LLC
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $213,000.0 - $263,000.0
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Computer Programming, Data Files, Distributed Systems, Home Automation, Machine Learning, Systems Development Life Cycle, Azure Machine Learning, Software Engineering, Large Language Models, Low Latency, Data Management, Machine Learning Operations
- **Published:** August 21, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-bulk-interactive-inference-mountain-view-ca--1f617dd5-38d1-4d5e-a41c-5da67fa127d8

## About the Role

* 5+ years of professional experience in the field of software engineering
 * Experience in programming C++
 * Experience with building highly scalable distributed system

We prefer:

 * Passionate about building internal infra and tools
 * Experience with building model hosting and inference solutions
 * Experience with handling datasets in the order of exabytes, Autonomous Driving Systems, C++ Programming Language, Cost Control, Data Management, Data Sets, Distributed Computing, High Tech Industry, High Throughput, Home Automation, Process Improvement, Scalable System Development, Software Engineering, Systems Scalability, Team Player, Use Cases

## Description

The ML Ops team, part of Waymo ML Platform team, builds tools and infrastructure to realize the ML flywheel at Waymo. This includes building automation and orchestration solutions to make complex ML workflows manageable and reliable. This team also partners closely with the modeling team to realize solutions to speed up developer velocity., We're looking for a software engineer to join the team to build and maintain the critical data and ML pipelines that powers ML development at Waymo.

In this hybrid role, you will report to the Head of ML Platform- Senior Staff Software Engineer.

You will:

 * Develop Waymo''s inference platform to make it scalable, high throughput, and low latency
 * Work closely with other teams across Waymo in hosting both internal and external ML models, including LLMs
 * Improving the efficiency of running inference on these large models to increase throughput and save cost
 * Deploy and integrate model inference solutions across a variety of use cases, such as distillation, eval, dataset generation, active learning, and auto-labeling


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