In this Associate Machine Learning Engineer role, you will help build and operate the machine learning infrastructure behind TikTok USDS JV feed and e-commerce recommendations. The work centers on production MLOps, real-time streaming, and feature stores that enable large-scale deep learning models, with a strong emphasis on monitoring, evaluation, and deployment reliability. You will collaborate with researchers and platform teams to move model ideas into zero-downtime serving.
The team is focused on applied machine learning for general feed recommendations and e-commerce experiences, translating new algorithms and techniques into measurable improvements in user engagement and satisfaction.
What you’ll do
- Design, build, and maintain robust MLOps pipelines (including CI/CD for ML) for hyper-scale recommendation models serving 10M–100M+ users, supporting continuous training, automated evaluation, and reliable deployment.
- Architect high-throughput real-time streaming data pipelines and feature stores, including offline and online feature synchronization, to power short-term and long-term user interest modeling.
- Optimize candidate generation and ranking predictive models for production serving, including CTR and CVR.
- Improve inference performance through acceleration, model quantization, parallel computation, and latency reduction using C++/CUDA/TensorRT or similar frameworks.
- Develop automated tools for monitoring, debugging, and visualization to track feature drift, model performance degradation, data leakage, and GPU/CPU cluster utilization.
- Partner with algorithm researchers and platform teams to streamline the lifecycle of large-scale deep learning models from experimental prototypes to zero-downtime production.
What you bring
- Bachelor’s degree or higher in Computer Science or a related field.
- Strong programming and problem-solving skills.
- Basic understanding of MLOps concepts, including data preprocessing, Docker, model tracking/versioning, and workflow orchestration.
- Motivation to tackle complex real-world distributed systems and machine learning operational challenges.
Technologies
- MLOps, CI/CD, Docker
- C++, CUDA, TensorRT
- CTR, CVR
Compensation and location
- Location: San Jose, CA (onsite)
- Salary: USD 122,574 - 259,200 per year
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)
- Eligible for additional discretionary bonuses/incentives and restricted stock units
Team focus
- Applied ML engineering and data science for general feed and e-commerce recommendations
- Developing innovative algorithms and techniques to improve engagement and satisfaction
- Applying large-scale machine learning to solve real-world problems
Preferred qualifications
- Experience in recommendation systems, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related areas
About USDS
TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps operated by the Joint Venture. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Its program includes comprehensive data privacy and cybersecurity safeguards to protect national security and secure U.S. user data, apps, and the algorithm, and it safeguards the U.S. content ecosystem for trust and safety decisions and moderation.
The company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.
Reasonable accommodation
USDS is committed to providing reasonable accommodations in 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, contact https://tinyurl.com/USDS-RA.
