ByteDance

2 days 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: 34 minutes agoStatus: Live

Job Summary

Work on ByteDance’s next-generation AI-native computing stack, owning research and system-building for the AI Compute layer and DPU. Tackle topics across LLM inference infrastructure—KV cache and multimodal serving, Kubernetes-native orchestration, scheduling and caching primitives, fault localization/observability, storage acceleration, vector retrieval engines, and heterogeneous power scheduling—bridging research breakthroughs into scalable production systems.

Location: Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Entry level

Key Responsibilities

•Conduct systematic research across the AI infrastructure stack to enable ultra-high performance and elasticity for LLM and AI-agent workloads.
•Develop or optimize infrastructure components for network and observability, including fault localization/root cause analysis and time-series database tuning.
•Build storage acceleration and serverless elastic file/storage architectures for AI scenarios, including hardware-software co-optimization for DPU.
•Research and design heterogeneous scheduling and power orchestration technologies for AI workloads, addressing heterogeneity and state dependencies.
•Optimize vector retrieval technologies and related cloud-native distributed index engines for low-latency, low-cost retrieval at ultra-large scale.

Key Requirements

•Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, focused on distributed and ML systems.
•Published first-author research in top venues (e.g., OSDI, SOSP, NSDI, NeurIPS, MLSys) with clear technical contributions.
•Demonstrated system-building ability with hands-on experience implementing or optimizing real systems beyond prototypes, with solid understanding of compute, network architecture, and operating systems.
•Deep expertise in at least one area such as LLM inference/AI-ML systems, AI system optimization (scheduling, observability, resource management, high-performance networking), or software-hardware co-design.
•Strong programming skills and ability to reason about complex system design; demonstrated ownership of significant research or systems work.

Experience:LLM inferenceDistributed systemsML systemsCloud-nativeKubernetesOpen sourceHigh-performance networking

Education:PhD / Doctorate

Skills:System-buildingResearchTechnical ownershipTechnical communicationRigorous reasoning

Tech Stack:KubernetesAIBrixLLM inferenceKV cacheMultimodal servingServerlessTime-series databasesVector retrievalDistributed vector index engineGPU virtualizationRDMADPDKNCCLOVSSR-IOVEBPFFPGAASICHigh-speed interconnectsDistributed storage

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

2 days 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: 34 minutes agoStatus: Live

Job Summary

Location: Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Entry level

Key Responsibilities

•Conduct systematic research across the AI infrastructure stack to enable ultra-high performance and elasticity for LLM and AI-agent workloads.
•Develop or optimize infrastructure components for network and observability, including fault localization/root cause analysis and time-series database tuning.
•Build storage acceleration and serverless elastic file/storage architectures for AI scenarios, including hardware-software co-optimization for DPU.
•Research and design heterogeneous scheduling and power orchestration technologies for AI workloads, addressing heterogeneity and state dependencies.
•Optimize vector retrieval technologies and related cloud-native distributed index engines for low-latency, low-cost retrieval at ultra-large scale.

Key Requirements

•Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, focused on distributed and ML systems.
•Published first-author research in top venues (e.g., OSDI, SOSP, NSDI, NeurIPS, MLSys) with clear technical contributions.
•Demonstrated system-building ability with hands-on experience implementing or optimizing real systems beyond prototypes, with solid understanding of compute, network architecture, and operating systems.
•Deep expertise in at least one area such as LLM inference/AI-ML systems, AI system optimization (scheduling, observability, resource management, high-performance networking), or software-hardware co-design.
•Strong programming skills and ability to reason about complex system design; demonstrated ownership of significant research or systems work.

Experience:LLM inferenceDistributed systemsML systemsCloud-nativeKubernetesOpen sourceHigh-performance networking

Education:PhD / Doctorate

Skills:System-buildingResearchTechnical ownershipTechnical communicationRigorous reasoning

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