7 hours ago

Senior Production System Engineer (New York City)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Own the end-to-end production readiness and lifecycle management of ByteDance’s large-scale GPU infrastructure across self-built data centers. Lead evaluation, qualification, integration, and rollout of next-generation platforms (e.g., NVIDIA GB200/GB300 NVL72, Vera Rubin), driving fleet onboarding, monitoring, incident response, and long-term reliability. Partner across hardware, networking, storage, power, cooling, and vendors while building automation, telemetry, and AI-assisted operations tooling for scalable GPU operations.

Location: New York

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Seniority: Mid level

Key Responsibilities

•Lead evaluation, qualification, integration, and production rollout of next-generation GPU platforms (e.g., GB200/GB300 NVL72, B200/B300, Vera Rubin, rack-scale AI infrastructure).
•Define production readiness plans and launch criteria across server hardware, firmware, BMC, OS, drivers, GPU software stacks, networking, storage, security, telemetry, and operational tooling.
•Drive rack-scale integration and fleet operations with hardware, data center, network, storage, power, cooling, and vendor teams to improve availability, utilization, serviceability, and lifecycle management.
•Diagnose complex Linux, hardware, firmware, PCIe, NVLink/NVSwitch, network, storage, and memory issues; develop qualification, burn-in, benchmarking, health-check, and regression-testing frameworks.
•Build automation and actionable observability telemetry for provisioning, configuration, monitoring, fault detection, remediation, repair, and lifecycle operations; provide on-call leadership during critical incidents and coordinate root-cause analysis and preventive actions.

Travel: Low travel

Key Requirements

•5+ years in production systems, infrastructure engineering, Site Reliability Engineering, DevOps, hardware systems engineering, or large-scale data center operations.
•Hands-on experience introducing and productionizing large-scale GPU infrastructure, including hardware NPI and/or fleet onboarding through qualification, integration, deployment, and post-launch reliability.
•Deep Linux administration and troubleshooting with strong understanding of server architecture and management technologies (kernels, drivers, BIOS/UEFI, BMC, Redfish, firmware, PCIe, NVMe, NICs, DPUs, hardware telemetry).
•Hands-on experience deploying or supporting distributed AI training/inference workloads in containerized and orchestrated environments, including CUDA, GPU drivers, NCCL, NVLink/NVSwitch, RDMA, InfiniBand/RoCE, or high-performance Ethernet.
•Proficiency in Python, Go, Bash (or similar) for production-grade infrastructure automation, plus experience applying AI/LLMs to engineering workflows like incident analysis and automated remediation.

Experience:AI infrastructureData centersDevOpsSite Reliability EngineeringHardware lifecycle management

Education:Bachelor's

Skills:Systems-thinkingTechnical leadershipCommunication

Languages:English

Tech Stack:LinuxNVIDIA GB200NVIDIA GB300NVL72HGXDGX B200DGX B300Vera RubinCUDANCCLNVLinkNVSwitchRDMAInfiniBandRoCEHigh-performance EthernetPythonGoBashKernels

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

Loading job details...

Preparing the role view and application actions.

ByteDance

7 hours ago

Senior Production System Engineer (New York City)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: New York

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Seniority: Mid level

Key Responsibilities

•Lead evaluation, qualification, integration, and production rollout of next-generation GPU platforms (e.g., GB200/GB300 NVL72, B200/B300, Vera Rubin, rack-scale AI infrastructure).
•Define production readiness plans and launch criteria across server hardware, firmware, BMC, OS, drivers, GPU software stacks, networking, storage, security, telemetry, and operational tooling.
•Drive rack-scale integration and fleet operations with hardware, data center, network, storage, power, cooling, and vendor teams to improve availability, utilization, serviceability, and lifecycle management.
•Diagnose complex Linux, hardware, firmware, PCIe, NVLink/NVSwitch, network, storage, and memory issues; develop qualification, burn-in, benchmarking, health-check, and regression-testing frameworks.
•Build automation and actionable observability telemetry for provisioning, configuration, monitoring, fault detection, remediation, repair, and lifecycle operations; provide on-call leadership during critical incidents and coordinate root-cause analysis and preventive actions.

Travel: Low travel

Key Requirements

•5+ years in production systems, infrastructure engineering, Site Reliability Engineering, DevOps, hardware systems engineering, or large-scale data center operations.
•Hands-on experience introducing and productionizing large-scale GPU infrastructure, including hardware NPI and/or fleet onboarding through qualification, integration, deployment, and post-launch reliability.
•Deep Linux administration and troubleshooting with strong understanding of server architecture and management technologies (kernels, drivers, BIOS/UEFI, BMC, Redfish, firmware, PCIe, NVMe, NICs, DPUs, hardware telemetry).
•Hands-on experience deploying or supporting distributed AI training/inference workloads in containerized and orchestrated environments, including CUDA, GPU drivers, NCCL, NVLink/NVSwitch, RDMA, InfiniBand/RoCE, or high-performance Ethernet.
•Proficiency in Python, Go, Bash (or similar) for production-grade infrastructure automation, plus experience applying AI/LLMs to engineering workflows like incident analysis and automated remediation.

Experience:AI infrastructureData centersDevOpsSite Reliability EngineeringHardware lifecycle management

Education:Bachelor's

Skills:Systems-thinkingTechnical leadershipCommunication

Languages:English

Tech Stack:LinuxNVIDIA GB200NVIDIA GB300NVL72HGXDGX B200DGX B300Vera RubinCUDANCCLNVLinkNVSwitchRDMAInfiniBandRoCEHigh-performance EthernetPythonGoBashKernels

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