Student Researcher - Compiler (Seed Infra) - 2026 Start (PhD)

ByteDance
San Jose
Workplace: OnsiteInternshipFunction: Research & Scientific (R&D)Education: phdSkills: ["Collaboration","Analysis"]

Join the Seed Infrastructures team to improve AI foundation model training and inference through compiler and systems optimizations. You’ll build and extend MLIR-based compiler passes, optimize execution across GPU and NPU accelerators, and support deployment pipelines from compilation through runtime integration. Work with large-scale training/inference acceleration techniques, and benchmark and analyze performance across hardware backends while collaborating with researchers to translate model requirements into compiler and runtime improvements.

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FursaFursa
ByteDance
ByteDance
7 hours ago

Student Researcher - Compiler (Seed Infra) - 2026 Start (PhD)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 day agoStatus: Live

Job Summary

Join the Seed Infrastructures team to improve AI foundation model training and inference through compiler and systems optimizations. You’ll build and extend MLIR-based compiler passes, optimize execution across GPU and NPU accelerators, and support deployment pipelines from compilation through runtime integration. Work with large-scale training/inference acceleration techniques, and benchmark and analyze performance across hardware backends while collaborating with researchers to translate model requirements into compiler and runtime improvements.
Location: San Jose
Workplace: Onsite
Employment Type: Internship · Permanent
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Contribute to AI compiler optimizations for training and inference workloads.
  • •Develop and extend MLIR-based compiler passes for graph lowering, optimization, and code generation.
  • •Optimize model execution on GPU and NPU accelerators for performance, memory efficiency, and scalability.
  • •Support model deployment pipelines, including compilation, packaging, and runtime integration.
  • •Benchmark, profile, and analyze performance of large-scale models across different hardware backends.

Key Requirements

  • •Currently pursuing a PhD in Computer Science, Electrical Engineering, or a related technical field.
  • •Experience using or developing open source LLM inference frameworks such as vLLM or SGLang, and proficiency in at least one deep learning framework (PyTorch, Megatron, DeepSpeed, or JAX) with inference workflows.
  • •Understanding of modern computing systems (hardware, storage, networking) and their impact on ML workloads.
  • •Familiarity with compilers or model optimization pipelines (e.g., PyTorch Dynamo) or related model execution workflows.
  • •Ability to commit to working for 12 weeks in 2026.
Experience:Large-scale MLOpen source
Education:PhD / Doctorate in Computer Science, Electrical Engineering, or related technical fields
Skills:CollaborationAnalysis
Tech Stack:MLIRVLLMSGLangPyTorchMegatronDeepSpeedJAXPyTorch DynamoTorch.fxXLACUDATritonNCCLRDMAFSDPGSPMD

Company Brief

ByteDance
Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Headquarters: Beijing, China
Founded: 2012
WebsiteLinkedIn