ML Infrastructure Engineer - New Grad

SambaNova Systems, Inc.
Austin, TX, United States
6 days ago
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Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Experience level
Starter
Compensation
$131,200.0 - $196,800.0
Working hours
Regular working hours

Tech stack

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
+12 more
Graphics Processing Unit (GPU) Pytorch Large Language Models Concurrency Caching Backend Information Technology Low Latency SGLang Machine Learning Operations TensorRT Decoding

Job 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

Requirements

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

Benefits & conditions

SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

About the company

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova’’s technology is the RDU (Reconfigurable Dataflow Unit) - a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value.

About the Team

The ML Infrastructure team builds and operates the inference stack that serves SambaNova’’s models on our RDU accelerators. We cover request scheduling, caching, decoding techniques, public APIs, and the accuracy testing that every inference feature must pass before it ships.

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