Machine Learning Engineer Graduate ( Vertical Recommendation) - 2027 Start
Listed on 2026-08-18
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Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Discover a career that energizes and excites you every day.
@2026 Tik Tok
Technology
Machine Learning Engineer Graduate (Tik Tok Vertical Recommendation) - 2027 StartLocation:
San Jose
Employment Type:
Regular
Job Code:
A172736A
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Responsibilities
About the Team The Recommendation Architecture team powers personalized recommendations for Tik Tok's vertical businesses. Our team consists of machine learning engineers and system engineers who support and innovate on production recommendation models serving hundreds of millions of users. We work at the intersection of machine learning and large-scale distributed systems, in a fast-paced, collaborative and impact-driven culture where your work directly shapes what users discover on Tik Tok every day.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
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.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Implement, train, and iterate on retrieval and ranking models (candidate generation, coarse/fine ranking, re-ranking) for Tik Tok vertical-business recommendation scenarios, in close partnership with algorithm teams.
- Deliver end-to-end machine learning engineering solutions: from model implementation and feature engineering on large-scale user behavior data to online deployment.
- Run and analyze A/B experiments; drive launches that improve core business metrics.
- Productionize state-of-the-art techniques such as sequence modeling, multi-task/multi-objective learning, and LLM-enhanced recommendation in large-scale systems.
- Collaborate closely with algorithm teams, backend engineers, data scientists, and product teams.
Qualifications
Minimum Qualifications
- Individuals who are completing or have recently completed a Bachelor's degree in Computer Science or a related discipline.
- Solid foundation in data structures, algorithms, and machine learning fundamentals.
- Proficiency in at least one general-purpose programming language such as Python, C++, Go, or Java.
- Strong communication and collaboration skills; curiosity about technology and problem-solving.
Preferred Qualifications
- Internship or research experience in recommendation, search, or ads; publications in relevant venues are a plus.
- Hands-on experience with a deep learning framework such as PyTorch or Tensor Flow.
- Experience with large-scale data processing (Spark/Flink) or distributed model training.
- Agile and quick learner with self-motivation, a sense of ownership, and creative problem-solving abilities.
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.
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