AI Infrastructure Engineer - Recommendation & LLM

TikTok; San Jose (CA); On-site; USD 128,000 - 317,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) with match

Parental leave

Disability insurance

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid personal time

Job summary

TikTok is seeking experienced Software Engineers / ML Systems Engineers to join our Model Infrastructure team in San Jose. You will help build the next generation of AI infrastructure powering our For You recommender system and foundation models, handling training, serving, and optimization at massive scale.

As part of a cross-disciplinary team, you will optimize GPU usage, design distributed training pipelines, and collaborate with researchers to bring state-of-the-art models into production

Qualifications

• Bachelor's, Master's, or Ph.D. in CS/CE or related field, or equivalent practical experience.
• 3+ years of software engineering, ML systems, distributed systems experience.
• Proficient in C++ or Python and building production-quality software.
• Experience with PyTorch, TensorFlow, or similar ML frameworks.
• Experience designing large-scale production systems.
• Strong problem-solving and independent project ownership.

Responsibilities

• Design, develop, and optimize large-scale AI training and online inference infrastructure for recommendation models and LLMs.
• Drive architecture of distributed training and serving systems with high scalability, reliability, and efficiency.
• Optimize end-to-end model performance across GPU compute, memory, networking, and runtime systems.
• Develop and optimize LLM training and serving infrastructure, including model parallelism, KV Cache, Continuous Batching, and efficient inference.
• Work closely with researchers and algorithm engineers to productionize new model architectures and algorithms.
• Identify and resolve performance bottlenecks across the full AI stack, from model and framework to GPU kernels and distributed runtime.
• Improve system latency, throughput, GPU utilization, scalability, and infrastructure cost efficiency.
• Drive technical design, implementation, performance benchmarking, and production rollout of critical infrastructure components.
• Mentor junior engineers and contribute to the team's technical direction and engineering standards.

Skills

C++

Python

Distributed systems

Problem solving

GPU optimization

Education

Bachelor's/Master/PhD in CS or related field

Tools

PyTorch

TensorFlow

CUDA

Triton

KV Cache

Job description

Location

San Jose

Employment Type

Regular

Job Code

A245171

About the Team

We are looking for experienced Software Engineers / ML Systems Engineers to join our Model Infrastructure team and build the next generation of AI infrastructure powering TikTok's For You recommendation system and Large Language Models (LLMs).Our team develops the core training and serving infrastructure behind one of the world's largest recommendation systems, enabling billions of personalized recommendations every day. We are also building next-generation infrastructure for foundation models and LLMs, covering large-scale model training, online inference, GPU optimization, distributed systems, and AI serving.As a member of the team, you will take ownership of challenging infrastructure problems at massive scale, working across model, framework, runtime, GPU, distributed systems, and production serving. You will collaborate closely with researchers, algorithm engineers, and infrastructure teams to turn state-of-the-­art AI technologies into highly scalable, reliable, and efficient production systems.This role is ideal for engineers who are passionate about AI systems, distributed computing, GPU optimization, Recommendation, LLMs, and building high-performance infrastructure at massive scale.

Responsibilities

• Design, develop, and optimize large-scale AI training and online inference infrastructure for recommendation models and LLMs.
• Drive the architecture and implementation of distributed training and serving systems with high scalability, reliability, and efficiency.
• Optimize end-to-end model performance across GPU computation, communication, memory, networking, and runtime systems.
• Develop and optimize LLM training and serving infrastructure, including model parallelism, KV Cache, Continuous Batching, and efficient inference.
• Work closely with researchers and algorithm engineers to productionize new model architectures and algorithms.
• Identify and resolve performance bottlenecks across the full AI stack, from model and framework to GPU kernels and distributed runtime.
• Improve system latency, throughput, GPU utilization, scalability, and infrastructure cost efficiency.
• Drive technical design, implementation, performance benchmarking, and production rollout of critical infrastructure components.
• Mentor junior engineers and contribute to the team's technical direction and engineering standards.

Qualifications

• Minimum Qualifications- Bachelor's, Master's, or Ph.D. degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of software engineering, ML systems, distributed systems, or related industry experience.
• Strong programming skills in C++ or Python and experience building production-quality software.
• Strong understanding of data structures, algorithms, operating systems, distributed systems, or computer architecture.
• Hands-on experience with PyTorch, TensorFlow, or other machine learning frameworks.
• Experience designing, developing, or optimizing large-scale production systems.
• Strong problem-solving skills and the ability to independently drive complex technical projects.
• Preferred Qualifications- Experience building infrastructure for large-scale recommendation systems, LLMs, or foundation models.
• Strong understanding of distributed training and model parallelism, including DP, TP, PP, FSDP, ZeRO, or related technologies.
• Hands-on experience with GPU programming and optimization, including CUDA, Triton, GPU kernels, or similar technologies.
• Experience with LLM inference and serving, including KV Cache, Continuous Batching, FlashAttention, CUDA Graph, speculative decoding, or related techniques.
• Experience optimizing GPU utilization, memory efficiency, communication performance latency, and throughput at scale.
• Experience with distributed systems, high-performance computing, networking, or ML infrastructure.
• Experience designing and owning large-scale production systems from architecture through deployment and operation.
• Contributions to open-source projects, research publications, or technical projects in machine learning systems, distributed systems, GPU computing, or LLM infrastructure.
• Experience mentoring engineers or leading technical projects is a plus.

Job Information

The base salary range for this position in the selected city is $128000 - $316800 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:

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

About TikTok

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.

Why Join Us

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.

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. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. 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

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.

TikTok Accommodation

TikTok 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

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