Senior Software Engineer, ML Infrastructure - USDS

Responsibilities

About the Team:
The USDS JV – PaCI (Platform and Community Integrity) Foundation team builds scalable ML infrastructure and AI platforms that form the backbone of Tik Tok's risk control intelligence, powering the entire lifecycle of integrated business controls for US users from large‑scale model training and deployment to real‑time inference and A/B testing.

Scope:
We develop cutting‑edge AI infrastructure and LLM applications, including autonomous AI agents, high‑performance LLM inference services, and specialized monitoring systems, to create a safer, smarter, and more trustworthy ecosystem for millions of users worldwide.

Opportunity:
Joining this team offers a unique perspective on Tik Tok’s core risk control strategy, tackling first‑seen challenges in a rapidly evolving product ecosystem and developing novel solutions.

• Scalable ML Systems – Design and maintain infrastructure for building, deploying, and serving risk defense algorithms at the US or global level.
• System Optimization – Drive the evolution of risk prevention and remediation capabilities, reducing latency and improving throughput for core business lines such as Live, Social, and Account Safety.
• Automation & Analytics – Build robust ML tools and automated procedures to streamline risk analytics and enhance defense enforcement efficiency.
• Trust & Compliance – Ensure all risk control solutions remain state‑of‑the‑art regarding data security, modularization, privacy, and global compliance standards.

• Bachelor's degree in Computer Science or a related field.
• 3+ years of experience designing, building, and maintaining large‑scale distributed systems.
• Proficiency in one or more general‑purpose languages such as Go, C/C++, Java, or Python.
• Ability to think critically and decompose complex, ambiguous problems into clear, concise technical solutions.
• Exceptional communication skills with a history of working effectively in cross‑functional, multi‑regional environments.

• MS or PhD in Computer Science, Computer Engineering, or a related technical field.
• Hands‑on experience with ML infrastructure or AI infrastructure handling massive traffic (e.g., feature stores, model serving, or specialized hardware acceleration).
• Background in Risk, Anti‑Fraud, AI Safety, or Trust & Safety domains.

The base salary range for this position in the selected city is $136,800 – $359,720 annually. Compensation may vary outside of this range based on qualifications, skills, competencies, and experience. In addition to base pay, this role may be eligible for discretionary bonuses/incentives and restricted stock units.

Benefits include 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, and paid holidays and personal time. Employees 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).