ByteDance

1 day ago

Research Scientist - AI Compute & DPU - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Conduct PhD-level research for an AI infrastructure team that owns the AI Compute layer and DPU, including the open-source Kubernetes-native control plane AIBrix. Work on systematic research across the full stack—network observability, storage systems, data center power scheduling, vector retrieval, and AI-agent-driven intelligence—aiming to improve performance, cost efficiency, latency, and elastic scaling for large-scale LLM workloads.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Graduate level

Key Responsibilities

•Perform systematic research across the AI infrastructure stack to address ultra-high performance and elasticity needs of LLM and AI-agent workloads.
•Research intelligent fault localization, root cause analysis, and time-series database tuning to improve large-scale cluster stability.
•Develop serverless high-performance elastic storage systems and storage-acceleration architectures for AI scenarios, including hardware-software co-optimization for DPU.
•Design heterogeneous collaborative GPU/CPU/MEM scheduling and power orchestration systems, addressing scheduling challenges with heterogeneous workloads and state dependencies.
•Optimize vector retrieval technologies for low-latency, low-cost ultra-large-scale vector retrieval using a cloud-native distributed vector index engine.

Key Requirements

•Completing or recently completed PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, focused on distributed and ML systems.
•Proven first-author publications in top venues with clear technical contributions.
•Strong system-building ability with hands-on experience implementing or optimizing real systems beyond prototypes.
•Solid understanding of compute, network architecture, and operating systems.
•Deep expertise in at least one area: LLM inference/AI-ML systems, AI system optimization (scheduling, observability, resource management, high-performance networking), or software-hardware co-design.

Education:PhD / Doctorate

Skills:System-buildingResearchOwnershipTechnical communicationRigorous reasoning

Tech Stack:KubernetesAIBrixLLM inferenceKV cacheMultimodal servingKubernetes-native control planeNetworkingRDMADPDKNCCLOVSSR-IOVEBPFFPGAASICVector retrievalVector index engine

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

Website LinkedIn

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ByteDance

1 day ago

Research Scientist - AI Compute & DPU - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Graduate level

Key Responsibilities

•Perform systematic research across the AI infrastructure stack to address ultra-high performance and elasticity needs of LLM and AI-agent workloads.
•Research intelligent fault localization, root cause analysis, and time-series database tuning to improve large-scale cluster stability.
•Develop serverless high-performance elastic storage systems and storage-acceleration architectures for AI scenarios, including hardware-software co-optimization for DPU.
•Design heterogeneous collaborative GPU/CPU/MEM scheduling and power orchestration systems, addressing scheduling challenges with heterogeneous workloads and state dependencies.
•Optimize vector retrieval technologies for low-latency, low-cost ultra-large-scale vector retrieval using a cloud-native distributed vector index engine.

Key Requirements

•Completing or recently completed PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, focused on distributed and ML systems.
•Proven first-author publications in top venues with clear technical contributions.
•Strong system-building ability with hands-on experience implementing or optimizing real systems beyond prototypes.
•Solid understanding of compute, network architecture, and operating systems.
•Deep expertise in at least one area: LLM inference/AI-ML systems, AI system optimization (scheduling, observability, resource management, high-performance networking), or software-hardware co-design.

Education:PhD / Doctorate

Skills:System-buildingResearchOwnershipTechnical communicationRigorous reasoning

Tech Stack:KubernetesAIBrixLLM inferenceKV cacheMultimodal servingKubernetes-native control planeNetworkingRDMADPDKNCCLOVSSR-IOVEBPFFPGAASICVector retrievalVector index engine

Company Brief

ByteDance

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn