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

ByteDance
San Jose
Workplace: OnsiteInternshipFunction: Research & Scientific (R&D)Education: phdSkills: ["Collaboration","Performance analysis","Problem-solving","Systems thinking"]

Work on AI compiler optimizations for training and inference, extending 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 deployment pipelines and distributed training/inference acceleration, and benchmark/profile large-scale models across hardware backends while collaborating with researchers to translate requirements into compiler and runtime improvements.

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FursaFursa
ByteDance
ByteDance
1 month ago

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

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 30 days agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Work on AI compiler optimizations for training and inference, extending 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 deployment pipelines and distributed training/inference acceleration, and benchmark/profile large-scale models across hardware backends while collaborating with researchers to translate requirements into compiler and runtime improvements.
Location: San Jose
Workplace: Onsite
Employment Type: Internship
Job Function: Research & Scientific (R&D)
Seniority: Intern level

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 with a focus on 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
  • •Proficiency in at least one deep learning framework (e.g., PyTorch, Megatron, DeepSpeed, JAX) with model inference workflow experience
  • •Understanding of modern computing systems (hardware, storage, networking) and their impact on ML workloads
  • •Ability to commit to working for 12 weeks in 2026
Education:PhD / Doctorate
Skills:CollaborationPerformance analysisProblem-solvingSystems thinking
Tech Stack:MLIRPyTorchMegatronDeepSpeedJAXVLLMSGLangPyTorch DynamoTorch.fxXLAGPUNPUCUDATritonNCCLRDMAFSDPGSPMD

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