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# ML Infrastructure Engineer - New Grad

- **Company:** SambaNova Systems, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Starter
- **Salary:** $131,200.0 - $196,800.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computer Programming, Data Structures, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Open Source Technology, Regression Testing, Software Engineering, Scripting, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Concurrency, Caching, Backend, Information Technology, Low Latency, SGLang, Machine Learning Operations, TensorRT, Decoding
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ml-infrastructure-engineer-new-grad-austin-tx--91f8581b-821b-4f48-8d37-0d1ee331c609

## About the Role

Artificial Intelligence (AI), GPU (Graphics Processing Unit), Energy Efficiency, Performance Modeling, Precision Testing, Application Programming Interface (API), Caching, Regression Testing, Python Programming/Scripting Language, Software Engineering, * B.S. in Computer Science, Electrical Engineering, or related field

 * Strong programming skills in Python
 * Understanding of algorithms, data structures, concurrency, and systems design
 * Coursework or project experience in distributed systems or machine learning
 * Experience with LLM serving frameworks such as vLLM, SGLang, or TensorRT-LLM
 * Experience with inference techniques such as speculative decoding, KV caching, or continuous batching
 * Experience with PyTorch

Preferred Qualifications

 * M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field
 * Experience building or maintaining APIs or backend services
 * Internship or research experience in ML systems or backend infrastructure
 * Experience with disaggregated systems - prefill/decode
 * Open source project ownership or contributions

## Description

As a new grad ML Infrastructure Engineer, you''ll write production Python for our inference serving stack, including our vLLM integration and public APIs. You''ll help bring features like speculative decoding, prompt caching, and tool calling into production on the RDU, and add accuracy and regression tests that catch problems before customers do.

Responsibilities

 * Implement inference features on the RDU such as speculative decoding, constrained decoding, tool calling, prompt caching, and long-context inference
 * Adapt vLLM and related serving frameworks to the RDU architecture
 * Build and maintain endpoints in the public inference API
 * Write accuracy verification and regression tests for inference features
 * Debug latency, throughput, and reliability issues in production services