Senior Production System Engineer - San Jose

ByteDance; San Jose (CA); On-site; USD 122,000 - 272,000; Full time

Job summary

ByteDance seeks an experienced Senior Production Systems Engineer to lead the introduction and productionization of large-scale GPU infrastructure. You will own platform evaluation, system integration, data center readiness, deployment validation, fleet onboarding, monitoring, and incident response across global data centers.

The role requires strong Linux skills, hardware lifecycle management, and automation experience, with cross-functional collaboration across engineering, data centers, and

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5+ years of experience 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 on platforms such as NVIDIA GB200/GB300 NVL72, HGX or DGX B200/B300.
• Deep knowledge of Linux administration, server architecture, and management tech including BIOS/UEFI, BMC, Redfish, firmware, PCIe, NVMe, NICs, DPUs, telemetry, and diagnostics.
• Experience deploying distributed AI workloads using containerized/orchestrated environments with CUDA, NCCL, NVLink/NVSwitch, RDMA/InfiniBand, or high-performance Ethernet.

Responsibilities

• Lead GPU platform introduction, qualification, integration, and production rollout.
• Define launch criteria and readiness plans for server hardware, firmware, drivers, and software stacks.
• Collaborate across data center, network, storage, and vendor teams to improve fleet availability and lifecycle management.
• Diagnose and resolve Linux/hardware/firmware issues; develop benchmarks and health checks.
• Build automation and telemetry for provisioning, monitoring, and remediation; apply AI for incident triage and remediation.
• Establish engineering standards, procedures, and long-term support models; mentor engineers.
• Participate in global on-call rotation and lead incident investigations.

Skills

GPU platforms

Linux administration

Automation

Python

Go

Bash

Hardware lifecycle

Site Reliability Engineering

Incident response

Education

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Information Technology, or related field

Tools

Kubernetes GPU Operator

Slurm

Ansible

Redfish

PCIe/NVMe

Job description

Responsibilities

The Server Management DevOps team is responsible for the end-to-end lifecycle management of servers across ByteDance’s self-built data centers in the United States and Europe.

Our scope covers new hardware introduction, data center delivery, production operations, hardware maintenance, configuration and firmware changes, capacity migration, asset decommissioning, data sanitization, and hardware reuse.

The team serves as a central engineering and coordination point across multiple functions, including:

• Hardware New Product Introduction (NPI)
• Server and data center operations
• Field maintenance and infrastructure management
• Hardware vendors and service providers
• Supply chain and asset management
• Infrastructure platform and automation engineering teams

As ByteDance continues to expand its AI infrastructure, the team is taking on an increasingly important role in introducing, productionizing, and operating high-density GPU platforms at scale.

About the Role

We are looking for an experienced and hands-on Senior Production Systems Engineer with deep expertise in large-scale GPU infrastructure, Linux systems, hardware lifecycle management, automation, and production operations.

In this role, you will lead the introduction and productionization of current- and next-generation AI infrastructure, including rack-scale and high-density GPU platforms such as NVIDIA GB200/GB300 NVL72, HGX or DGX B200/B300, Vera Rubin NVL72, and comparable accelerator systems. You will own critical work across platform evaluation, system and firmware integration, data center readiness, deployment validation, fleet onboarding, monitoring, incident response, and long-term operational reliability. You will also work directly with AI training and inference environments to ensure that the underlying infrastructure meets real workload requirements.

This is a senior individual-contributor role requiring strong technical judgment, hands-on engineering ability, and the capacity to lead complex global infrastructure initiatives across organizational boundaries.

Key Responsibilities

• Advanced GPU Platform Introduction: Lead the evaluation, qualification, integration, and production rollout of next-generation GPU platforms, including GB200/GB300 NVL72, B200/B300 systems, Vera Rubin, and future rack-scale AI infrastructure.
• End-to-End Production Readiness: Define launch criteria and readiness plans spanning server hardware, firmware, BMC, operating systems, drivers, GPU software stacks, networking, storage, security, telemetry, and operational tooling.
• Rack-Scale Integration and Fleet Operations: Partner across hardware, data center, network, storage, power, cooling, and vendor teams to resolve system-level challenges and improve GPU fleet availability, utilization, serviceability, and lifecycle management.
• Systems, Performance, and Reliability Engineering: Diagnose complex Linux, hardware, firmware, PCIe, NVLink/NVSwitch, network, storage, and memory issues, while developing qualification, burn-in, benchmarking, health-check, and regression-testing frameworks. Improve the availability, utilization, serviceability, and lifecycle management of large GPU fleets across multiple data center regions.
• Automation, Observability, and AI-Assisted Operations: Build scalable automation and actionable telemetry for provisioning, configuration, monitoring, fault detection, remediation, repair, and lifecycle operations; apply AI technologies to incident triage, troubleshooting, knowledge retrieval, and automated remediation.
• Technical and Cross-Functional Leadership: Establish engineering standards, operational procedures, and long-term support models; mentor engineers and drive complex infrastructure programs across internal teams, supply-chain partners, and external vendors.
• On-Call and Global Operations: Participate in a global on-call rotation and provide senior-level leadership during critical production incidents. Occasional travel to data centers, integration facilities, or vendor sites may be required. Lead the investigation of complex and high-impact production incidents, coordinate mitigation across teams and vendors, perform root-cause analysis, and ensure that preventive actions are implemented and measured.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Information Technology, or a related field, or equivalent practical experience, with 5+ years of experience in production systems, infrastructure engineering, Site Reliability Engineering, DevOps, hardware systems engineering, or large-scale data center operations.
• Proven hands-on experience introducing and productionizing large-scale GPU infrastructure, including ownership of hardware NPI or fleet onboarding across qualification, system integration, deployment, production validation, operational handoff, and post-launch reliability. Experience must include a recent-generation platform such as NVIDIA GB200/GB300 NVL72, HGX or DGX B200/B300, or a technically comparable rack-scale AI system.
• Deep knowledge of Linux administration and troubleshooting, combined with a strong understanding of server architecture and management technologies such as kernels, drivers, BIOS/UEFI, BMC, Redfish, firmware, PCIe, NVMe, NICs, DPUs, hardware telemetry, and failure diagnostics.
• Hands-on experience deploying or supporting distributed AI training or inference workloads using containerized and orchestrated environments, with working knowledge of technologies such as CUDA, GPU drivers, NCCL, NVLink, NVSwitch, RDMA, InfiniBand, RoCE, or high-performance Ethernet. Familiarity with high-density data center requirements, including liquid cooling, power delivery, rack integration, structured cabling, network fabrics, and deployment safety.
• Proficiency in Python, Go, Bash, or another programming language for production-grade infrastructure automation, along with practical experience applying AI or large language models to engineering workflows such as incident analysis, troubleshooting, knowledge retrieval, code generation, or automated remediation.
• Experience building and operating monitoring, telemetry, hardware management, or automated remediation platforms at substantial scale, with measurable results in fleet availability, deployment efficiency, incident reduction, operational efficiency, or reliability.
• Strong systems-thinking, technical leadership, and communication skills, with the ability to troubleshoot across hardware and software layers and lead complex initiatives involving global teams, infrastructure partners, and vendors. Professional proficiency in English is required.

Preferred Qualifications

• Direct experience deploying and operating GB200 or GB300 NVL72 systems, including compute and NVLink switch trays, Grace CPUs, Blackwell GPUs, ConnectX networking, BlueField DPUs, rack management, firmware dependencies, power delivery, and liquid-cooled data center integration.
• Experience planning, qualifying, or preparing production and operational environments for next-generation platforms such as NVIDIA Vera Rubin NVL72.
• Experience operating large-scale GPU clusters across multiple data centers or geographic regions.
• Strong understanding of distributed AI workload behavior and performance analysis, including collective communication, multi-node training, inference serving, GPU scheduling, checkpointing, workload-related bottlenecks, DCGM, NCCL testing, CUDA profiling, and network-fabric telemetry.
• Experience with Kubernetes GPU Operator, Slurm, Ansible, configuration management, infrastructure as code, CI/CD, or large-scale provisioning and orchestration systems.
• Experience working directly with OEMs, ODMs, component suppliers, or GPU platform vendors throughout qualification, technical escalation, root-cause analysis, and corrective-action processes.
• Contributions to infrastructure engineering communities, technical publications, patents, open-source projects, or relevant industry standards.

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Reasonable Accommodation

ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $121600 - $272000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
• Exercising sound judgment.