General Hire) Multi-modal Machine Learning Engineer

Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. Our mission is to protect billions of users and publishers across the globe every day. We embrace the state-of-the-art machine learning technologies and scale them to moderate the tremendous amount of data generated on the platform. With the continuous efforts from our team, TikTok is able to provide the best user experience and bring joy to everyone in the world.

We are looking for excellent machine learning engineers who can take initiatives, design and develop advanced machine learning solutions, and deploy them directly to TikTok’s global platform. A successful candidate will have machine learning expertise and good software engineering experience. And you will take pride in working with engineers, product managers and business partners to identity and solve the most challenging safety and integrity problems in the internet scale.

You will be evaluated for five sub-teams working on various areas of Trust and Safety during the general hire process.

Responsibilities - What You’II Do

• Lead and build content understanding models for content moderation.
• Work on state-of-the-art content understanding techniques including but not limited to unimodal/multimodal content classifiers, graph models, representation learning models, and LLM.
• Collaborate with product teams to define business objectives and improve trust and safety strategy.
• Collaborate with engineering teams to deploy machine learning models, design online model workflow, and implement serving pipeline at scale.
• Collaborate with data scientist team to understand the key challenges and propose data-driven strategies.

BS/MS degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields, with 2+ years of related experience.

• Hands-on experience in one or more of the following areas: machine learning (CV/NLP/Multimodal/Graph/LLM), statistical models and applied mathematical methods.
• Strong coding skills, especially in Python and similar languages.
• Curiosity towards new technologies and entrepreneurship, good communication and teamwork skills., Experience in LLM, multimodal modeling, representation learning and/or publications in AI/ML conferences are a plus.
• Understanding of the business value of content understanding and content moderation.
• Experience in developing online ML systems including ranking, retrieval.

The base salary range for this position in the selected city is $162000 - $387600 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