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Machine Learning Engineer Graduate (Brand Ads) - 2027 Start

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Machine Learning Engineer Graduate (Brand Ads) - 2027 Start (PhD)

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TikTok

Machine Learning Engineer Graduate (Brand Ads) - 2027 Start

San Jose$128,000 – $256,000Posted Aug 4, 2026

Apply on company site View full job

Why you should apply for a job to TikTok:

4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Responsibilities

The Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting.

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:
- As a Machine Learning Engineer on the Brand Ads team, you will work on real-world problems such as forecasting available inventory, optimizing auction traffic, and using machine learning to improve delivery quality and efficiency. You will collaborate closely with engineers, product managers, data scientists, and strategy partners to turn ambiguous business challenges into scalable technical solutions.
-You will work on a brand-facing business where your systems map directly to revenue and to the experience of major advertisers.

Qualifications

Minimum Qualifications
- Individuals who are completing or have recently completed a Master's degree in Computer Science, a related field, or equivalent practical experience.
- Proficient in at least one general-purpose programming language, such as Go, C/C++, Java, or Python, with solid coding and debugging skills.
Strong foundation in data structures, algorithms, Linux development environment, and system design, with strong analytical and problem-solving skills.
- Solid understanding of statistics, probability, machine learning, and deep learning fundamentals, with familiarity with at least one mainstream machine learning framework such as TensorFlow, PyTorch, or MXNet.
- Ability to work effectively in ambiguous environments, make sound engineering trade-offs, and collaborate in cross-functional teams.

Preferred Qualifications
- Good understanding of online advertising systems, especially one or more of the following areas: guaranteed delivery, reservation ads, pacing, allocation, inventory forecasting, traffic strategy, brand safety, ads ranking, bidding, or auction systems.
- Familiarity with advertising concepts such as CPM, CPC, CTR, CVR, campaign, creative, targeting, demand, inventory, budget, pacing, reservation, auction, DSP, or RTB.
- Experience with large-scale backend systems, recommendation systems, search systems, or advertising systems.
- Experience with data analysis, experimentation, feature engineering, or model optimization.
- Experience with large-scale backend, recommendation, search, or advertising systems, as well as data analysis, experimentation, feature engineering, model optimization, distributed computing, or related internship, project, or research experience.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $128000 - $256000 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.

For 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.

Responsibilities

Qualifications

Qualifications

Minimum Qualifications
- Individuals who are completing or have recently completed a Master's degree in Computer Science, a related field, or equivalent practical experience.
- Proficient in at least one general-purpose programming language, such as Go, C/C++, Java, or Python, with solid coding and debugging skills.
Strong foundation in data structures, algorithms, Linux development environment, and system design, with strong analytical and problem-solving skills.
- Solid understanding of statistics, probability, machine learning, and deep learning fundamentals, with familiarity with at least one mainstream machine learning framework such as TensorFlow, PyTorch, or MXNet.
- Ability to work effectively in ambiguous environments, make sound engineering trade-offs, and collaborate in cross-functional teams.

Preferred Qualifications
- Good understanding of online advertising systems, especially one or more of the following areas: guaranteed delivery, reservation ads, pacing, allocation, inventory forecasting, traffic strategy, brand safety, ads ranking, bidding, or auction systems.
- Familiarity with advertising concepts such as CPM, CPC, CTR, CVR, campaign, creative, targeting, demand, inventory, budget, pacing, reservation, auction, DSP, or RTB.
- Experience with large-scale backend systems, recommendation systems, search systems, or advertising systems.
- Experience with data analysis, experimentation, feature engineering, or model optimization.
- Experience with large-scale backend, recommendation, search, or advertising systems, as well as data analysis, experimentation, feature engineering, model optimization, distributed computing, or related internship, project, or research experience.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

About TikTok

TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

Size: 10,000+ employees
Industry: Technology: Consumer Internet

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