Responsibilities

Tik Tok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security ("USDS") is a subsidiary of Tik Tok in the U.S.

TRAE (The Real AI Engineer) is an intelligent engineering product capable of understanding requirements, orchestrating tools, and independently completing development tasks, providing users with end-to-end software generation capabilities. As one of the most popular AI programming products and the world's first end-to-end AI software development agent, TRAE covers a full spectrum of development scenarios, from simple to highly complex. We are looking for passionate and creative engineers to join us in reshaping the development paradigm and defining the future of AI-driven software engineering.

We are seeking a Machine Learning Engineer to join the core R&D team of TRAE, responsible for model training, optimization, quantization, and deployment. You will work closely with top engineers and researchers to explore and implement LLM training and deployment for software engineering, driving the continuous evolution of TRAE's intelligent engineering capabilities.

• Design, train, and fine-tune large language models (LLMs) that support TRAE's core reasoning and code generation capabilities.
• Build efficient, stable, and scalable model training and evaluation pipelines.
• Collaborate with infrastructure and product teams to deploy and monitor models efficiently on GPU clusters.
• Continuously optimize models for latency, throughput, and accuracy.
• Stay up to date with and apply cutting-edge techniques in large model optimization and inference acceleration.

Qualifications

Minimum Qualifications

• Bachelor's degree or above in Computer Science, Electrical Engineering, Mathematics, or a related field.
• Solid foundation in machine learning, deep learning, and optimization algorithms.
• Proficiency in Py Torch or Tensor Flow, with programming skills in Python and C++/CUDA.
• Experience with large-scale distributed training, mixed-precision training, or model parallelism.
• Hands-on experience with model quantization, pruning, or CUDA-based deployment optimization.
• Passionate about building efficient, production-ready AI systems and advancing the future of AI-driven software development.

Preferred Qualifications

• Master's degree or above in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 3+ years of experience in tech.

Compensation

The base salary range for this position in the selected city is $136,800 - $359,720 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

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.

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; and
3. Exercising sound judgment.