Recommendation Architecture AI/ML Infrastructure Engineer Graduate (Data-Arch-TikTok Live) - 2027 Start

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates’ jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Online Assessment Candidates who pass resume screening will be invited to participate in Our Company’s technical online assessment.

Responsibilities

• Build and optimize infrastructure for large-scale model training and online inference.
• Develop distributed systems supporting large recommendation models and LLMs.
• Improve training and inference performance through GPU optimization and efficient communication.
• Collaborate with researchers to develop and deploy LLM training and serving solutions.
• Analyze system bottlenecks and implement performance optimizations.

• Individuals who are completing or have recently completed a Bachelor’s or Master’s degree in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.
• Strong programming skills in C++ or Python. *Good understanding of data structures, algorithms, and computer systems.
• Familiarity with PyTorch or TensorFlow.
• Knowledge of Transformer architectures and Large Language Models (LLMs).
• Strong problem-solving skills and a passion for building large-scale AI systems., * Hands-on experience with LLM training or inference through research, internships, or open-source projects. *Familiarity with distributed training concepts (e.g., DP, TP, PP, FSDP, ZeRO).
• Experience with GPU programming using CUDA, Triton, or similar technologies.
• Understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention. *Contributions to open-source projects or research in machine learning systems, distributed systems, or LLM infrastructure., 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

(part of ByteDance) 3.33.3 out of 5 stars San Jose, CA $128,000 - $256,000 a year, Pulled from the full job description

• Paid parental leave
• Parental leave
• Health insurance
• 401(k) matching
• Vision insurance
• Dental insurance
• Paid sick time, 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.

Our team develops the core training and serving infrastructure that powers one of the world’s largest recommendation systems, enabling billions of personalized recommendations every day. We are also advancing the next generation of AI infrastructure for foundation models and LLMs, driving innovation in large-scale model training, online inference, and GPU optimization. As part of the team, you will work on distributed training and inference systems, high-performance GPU computing, and scalable LLM infrastructure. You’ll collaborate closely with experienced engineers and researchers to transform cutting-edge AI technologies into production systems that directly impact the experience of hundreds of millions of TikTok users. This role is ideal for candidates who are passionate about LLM systems, distributed computing, GPU programming, and building AI systems at massive scale.We are looking for passionate talented individuals to join our Model Infrastructure team, building the next generation of infrastructure for TikTok’s For You recommendation system and Large Language Models (LLMs).

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth., TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok’s global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo., Inspiring creativity is at the core of TikTok’s mission. Our innovative product is 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 bring joy - a mission we work towards every day., TikTok 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 TikTok, our mission is to inspire creativity and bring joy. 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.