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

Machine Learning Engineer Graduate (Brand Ads) - 2027 Start (PhD) at TikTok in San Jose, CA.

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.
• 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.

Requirements

• Individuals who are completing or have recently completed a PhD degree in Computer Science or a related discipline.
• Solid programming skills in one or more general-purpose programming languages, including but not limited to Go, C/C++, Java, or Python.
• Familiarity with basic data structures, algorithms, and Linux development environment.
• Strong coding, debugging, and system design fundamentals.
• Strong analytical thinking skills and essential knowledge of statistics, probability, and machine learning fundamentals.
• Good theoretical grounding in machine learning and deep learning concepts and techniques.
• Familiarity with at least one mainstream machine learning framework, such as TensorFlow, PyTorch, or MXNet.
• Comfort with ambiguity and the judgment to make clear engineering trade-offs.
• Strong communication and collaboration skills, with the ability to work effectively in a cross-functional environment.

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 distributed computing or large-scale machine learning systems, such as Spark, Flink, TensorFlow, or similar platforms.
• Relevant internship, project, or research experience in advertising, recommendation, forecasting, optimization, or large-scale machine learning systems.

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)

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.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.

Additional Information

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.