Associate Machine Learning Engineer
TikTok USDS Joint Venture
Posted 15 Nov 2026, 14:09 ET
This job at a glance
- Who can apply
- New grads and up to 2 years · Bachelor's degree
- Must know
- Data structures & algorithmsCI/CDETLC++Deep learningDocker
- Nice to have
- Machine learningNLP
- Work
- On-site in San Jose
- Pay
- Not stated by the employer.
- Skill demand
- Data structures & algorithms27%ETL25%CI/CD20%C++17%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 15, 2026 · still open
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About the Role
We are a group of applied machine learning engineers and data scientists focusing on general feed recommendations and E-commerce recommendations. We develop innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested in applying large-scale machine learning to solve various real-world problems.
What You Will Do
- Participate in designing, building, and maintaining robust MLOps pipelines (CI/CD for ML) for hyper-scale (10M–100M+ users) recommendation models, ensuring reliable continuous training, automated evaluation, and seamless deployment.
- Architect high-throughput real-time streaming data pipelines and feature stores (offline & online feature synchronization) to support dynamic user interest modeling (short-term & long-term signals).
- Optimize candidate generation and ranking predictive models (CTR, CVR) for production serving. Work on inference acceleration, model quantization, parallel computation, and latency reduction using C++/CUDA/TensorRT or similar frameworks.
- Build automated monitoring, debugging, and visualization tools for tracking 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 prototype to zero-downtime production deployment.
Requirements & Tech Stack
- Bachelor's degree or higher in Computer Science or related fields.
- Strong programming and problem-solving ability.
- Basic understanding of MLOps principles, including data preprocessing, containerization (Docker), model tracking/versioning, or workflow orchestration.
- Driven to solve complex real-world distributed systems and machine learning operational challenges.
Preferred Qualifications
- Experience in recommendation systems, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.