Infrastructure Delivery Engineer Graduate (Server Delivery) - 2027 Start

Founded in 2012, ByteDance’s mission is to inspire creativity and enrich life. With a suite of products including TikTok, Lemon8, CapCut, and Pico, ByteDance makes it easier and more fun for people to connect with, consume, and create content.

About the role

The Global Server Delivery team builds and scales the physical infrastructure that powers the next generation of AI. Every year, we deploy gigawatts (GW) of compute capacity across global data centers, delivering thousands of CPU and GPU servers to support large-scale AI and cloud services. Our team owns the end-to-end delivery lifecycle—new platform introduction, infrastructure planning, power and cooling optimization, deployment execution, and operational readiness—focusing on maximizing power utilization, improving delivery efficiency, and ensuring the highest standards of quality and reliability. By combining engineering expertise with AI-driven analytics and automation, we continuously optimize infrastructure planning and operations at global scale.

Responsibilities

• AI Infrastructure Delivery: Participate in the deployment of next-generation CPU and GPU server platforms; learn server architecture, hardware components, power characteristics, and deployment requirements; support new platform introduction (NPI), system compatibility validation, and deployment readiness; assist in large-scale server rollout projects across global data centers.
• Capacity Planning & Engineering Analysis: Analyze server power consumption, rack capacity, cooling requirements, and infrastructure utilization; support capacity planning for data centers based on electrical and thermal constraints; build analytical models to optimize rack layouts, deployment efficiency, and resource utilization; identify operational risks and recommend engineering improvements.
• Project & Operations Management: Coordinate cross-functional teams including engineering, supply chain, facilities, vendors, and operations; track project schedules, deployment milestones, and delivery quality; manage deployment readiness, installation progress, and engineering documentation; support material planning and accessory management for large-scale deployments.
• AI-driven Engineering: Apply AI tools to improve engineering workflows; use AI to automate data processing, reporting, documentation, and root-cause analysis; analyze millions of operational records to identify trends, anomalies, and optimization opportunities; explore AI-assisted capacity forecasting, deployment planning, and intelligent operations.

Qualifications

Minimum Qualifications

• Completing or recently completed a Bachelor’s or Master’s degree in Computer Science, a similar technical field of study, or equivalent practical experience.
• Strong analytical and problem-solving skills.
• Curious mindset with willingness to learn complex systems.
• Good communication and teamwork skills.
• Comfortable working with data and solving engineering problems.

Preferred Qualifications

• Experience in one or more of the following: Python, SQL, or scripting languages; Excel data analysis and visualization; AI tools; data center infrastructure; server hardware; cloud computing.

Pay

The base salary range for this position is $76,000 – $128,000 annually. Compensation may vary outside of this range depending on qualifications, skills, competencies, experience, and location. Base pay is one part of the total package that may include additional discretionary bonuses/incentives and restricted stock units.

Benefits

• Day-one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).