Machine Learning Engineer Graduate (Recommendations and Search) - 2027 Start (PhD)

About the role

The Tech and Product team of TikTok USDS is missioned to empower TikTok US users to have a great user experience with strong data security and privacy protections, focusing on compliance, reliability, business and product support, and efficiency improvement. As part of this team, you will build and scale high-impact Machine Learning solutions—including recommendation engines, search relevance, and e-commerce systems—designed specifically to deliver personalized, high-performing experiences while ensuring world-class data governance, privacy compliance, and system security for US users.

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.

Responsibilities

Depending on the team that you'll be considered for, you can expect to:

• Design, build, train, and evaluate machine learning models for recommendation systems, search ranking, query understanding, or conversion prediction.
• Implement efficient pipelines for feature extraction, model training, evaluation, offline-to-online deployment, and A/B testing.
• Process and analyze massive user behavior data and catalog logs using distributed systems to construct real-time and offline features.
• Optimize online inference latency and system throughput for high-QPS production microservices.
• Conduct continuous A/B testing, analyze online metrics, identify bottleneck areas, and iterate on models to drive business goals.

Qualifications

Minimum Qualification(s): Individuals who are completing or have recently completed a PhD's degree in Computer Science, Engineering, Math, Statistics, or a related discipline. Solid background in Data Structures, Algorithms, Computer Systems, and Software Design. Strong theoretical understanding and practical knowledge of machine learning concepts.

Preferred Qualification(s): Experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields. Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.

Pay

The base salary range for this position in the selected city is $129,960 - $246,240 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).

Schedule

The company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.