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Urgent! Staff Machine Learning Engineer, TikTok Ads Core Global - Traffic & Strategy Job Opening In San Jose – Now Hiring TikTok

Staff Machine Learning Engineer, TikTok Ads Core Global Traffic & Strategy



Job description

TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a global business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel.

Ads Core Traffic Strategy & User Experience team is essential to TikTok’s success, our work focuses are: - Personalized Ads Experience: We optimize every stage of the ad delivery pipeline, from recall and ranking to final placement, by integrating user feedback to make ads more relevant and engaging.

- Cutting-Edge Multi-Scenario Integration: this includes building context models that analyze ads-related information and scene elements to improve accuracy, as well as developing list-wise models to optimize recommendation outcomes and ads ROIs. We’re looking for innovative Staff Machine Learning Engineers to develop state-of-art ad technologies, including ranking, retrieval, targeting, bidding, auction, etc.

You will be part of a team that's optimizing ads format and ranking strategies, and you will be responsible for bringing a better returns on investment for advertisers.

What will you do:
- Develop advanced ads delivery capabilities that leverage cutting-edge machine learning techniques, working closely with recommendation system teams to deliver personalized ads.

- Lead the rapid iteration and optimization of machine learning models to enhance TikTok’s overall revenue and system efficiency.
- Ensure that advertising models deliver high performance in terms of CTR, CVR, user engagement, and business ROIs. - Continuously improve bidding and budget optimization algorithms to help advertisers find the best-matching traffic for their needs.

- Work closely with product managers, data scientists, software engineers, and business teams to align machine learning solutions with business goals.
- Ensure that ads delivery systems are tailored to the needs of different verticals and global markets customers, driving measurable business impacts.



Minimum Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field.
- Hands-on experience with at least one mainstream machine learning framework, such as TensorFlow, PyTorch, or MXNet, including its architecture and implementation mechanisms.

- Solid domain knowledge in at least one of the following areas: search, ranking, recommendation systems, or monetization.

- Proven experience in optimizing machine learning models for performance, scalability, and business impacts.

- Sophisticated analytical and problem-solving skills, with the ability to break down complex problems and deliver effective technical solutions.
- Strong collaboration skills, with the ability to work effectively with cross-functional teams across different locations and time zones for global business needs.

Preferred Qualifications:
- In-depth understanding of online advertising concepts such as CPC, CPM, CTR, CVR, ranking, targeting, conversion, budgeting, campaigns, creatives, demand and inventory management, DSP, and RTB.
- Hands-on experience with large-scale distributed software systems such as Spark or TensorFlow for resource management and task scheduling.

- Excellent communication skills, with the ability to present complex technical concepts to both technical and non-technical audiences.

- Strong interest in improving user experience, ensuring that advertising models and delivery systems provide relevant and engaging content while respecting user preferences and privacy.


Required Skill Profession

Computer Occupations



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