ByteDance

1 day ago

Tech Lead, Research Scientist/Engineer - AI Infrastructure

✓ 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

Define and build next-generation AI infrastructure at ByteDance, translating evolving AI requirements into scalable architectures across compute, storage, networking, chips, power, and data/application layers. Own end-to-end AI factory architecture for large-scale training, RL, and inference, exploring emerging systems and hardware trends. Benchmark and optimize ML stack and AI memory systems for long-horizon agents, while aligning across research, engineering, hardware, and product teams.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and evaluate scalable AI factory architectures across compute, storage, networking, chips, power, and data/application layers for training, RL, and inference.
•Develop technical proposals that balance supply-chain and energy constraints with silicon and software trade-offs.
•Track and explore emerging trends across AI systems, distributed training/RL, and hardware acceleration, including cognitive-science and psychology influences on AI memory and reasoning.
•Analyze and optimize ML stack performance (scheduling, networking, storage, training/RL frameworks, and long-horizon AI memory) via benchmarking and bottleneck analysis.
•Collaborate across research, engineering, hardware, data-center, and product teams to translate workload requirements into scalable solutions and drive cross-team initiatives.

Key Requirements

•PhD (or recently completed) in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
•Experience in distributed systems, infrastructure engineering, or ML systems, including exposure to large-scale training or RL pipelines.
•Strong ability to integrate AI tools into knowledge discovery and research workflows.
•Ability to learn quickly and stay productive on a fast-evolving technical horizon.
•Excellent communication skills to collaborate across teams.

Experience:AI infrastructureDistributed systemsMachine learningRLHigh-performance computing

Education:PhD / Doctorate

Skills:CommunicationRapid learning

Tech Stack:AI infrastructureAI memory systemsDistributed trainingReinforcement learningRL pipelinesSchedulingHigh-performance networkingRDMANCCLGPUAcceleratorsKV cacheRetrieval-augmented architectures

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

Tech Lead, Research Scientist/Engineer - AI Infrastructure

✓ 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: Mid level

Key Responsibilities

•Design and evaluate scalable AI factory architectures across compute, storage, networking, chips, power, and data/application layers for training, RL, and inference.
•Develop technical proposals that balance supply-chain and energy constraints with silicon and software trade-offs.
•Track and explore emerging trends across AI systems, distributed training/RL, and hardware acceleration, including cognitive-science and psychology influences on AI memory and reasoning.
•Analyze and optimize ML stack performance (scheduling, networking, storage, training/RL frameworks, and long-horizon AI memory) via benchmarking and bottleneck analysis.
•Collaborate across research, engineering, hardware, data-center, and product teams to translate workload requirements into scalable solutions and drive cross-team initiatives.

Key Requirements

•PhD (or recently completed) in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
•Experience in distributed systems, infrastructure engineering, or ML systems, including exposure to large-scale training or RL pipelines.
•Strong ability to integrate AI tools into knowledge discovery and research workflows.
•Ability to learn quickly and stay productive on a fast-evolving technical horizon.
•Excellent communication skills to collaborate across teams.

Experience:AI infrastructureDistributed systemsMachine learningRLHigh-performance computing

Education:PhD / Doctorate

Skills:CommunicationRapid learning

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