Senior Machine Learning Engineer - Ads Pangle - USDS

About the Team Pangle is the ad network of TikTok for Business, helping mobile developers accelerate growth, deliver engaging ad experiences, and maximize revenue by accessing TikTok's global advertising demand. Operating in more than 36 countries and regions, Pangle has built a strong reputation for driving measurable results for app partners worldwide. As Pangle expands into the U.S. market, we’re building our advertising platform from the ground up — tackling exciting new challenges in large‑scale systems, optimization, and machine learning. Join us to shape the future of mobile monetization and grow your career in a fast‑moving, global team. Responsibilities Develop and optimize bidding algorithms and strategies across Pangle’s ad delivery systems, including targeting, retrieval, ranking, and bidding models, with a focus on improving monetization efficiency and overall ad ROI. Improve the performance and efficiency of large‑scale, online‑learning–based deep models for real‑time advertising applications. Apply advanced modeling techniques and strategic thinking to enhance attribution accuracy, delivery quality, and long‑term ecosystem sustainability. Identify and drive innovative commercialization technologies and product solutions. Design, build, and iterate on core ad prediction models such as CTR (Click‑Through Rate) and CVR (Conversion Rate) models. Qualifications Minimum Qualifications: Bachelor’s degree in computer science or related technical disciplines. 3+ years of hands‑on experience with building and training complex and scalable machine learning systems. Strong Computer Science fundamentals (algorithms, data structures, software design) and problem‑solving skills. Strong coding skills and a solid understanding of machine learning algorithms, particularly deep learning and ranking models. Experience leading or driving machine learning projects. Preferred Qualifications: Strong theoretical background in machine learning and deep learning, with proficiency in at least one major framework (e.g., TensorFlow, PyTorch). Demonstrated experience optimizing large‑scale advertising systems, including bidding algorithms and delivery strategies. Familiarity with OCPC, OCPM, and AEO bidding models, and understanding of ad delivery mechanisms. Excellent teamwork and communication skills, with a strong sense of ownership and the ability to move projects forward independently. Strong business and data intuition, passion for tackling complex problems, and proven ability in abstraction, project execution, and innovation. Job Information 【For Pay Transparency】Compensation Description (Annually). The base salary range for this position in the selected city is $177,688 - $341,734 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. EEO Statement 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: Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; Exercising sound judgment. #J-18808-Ljbffr TikTok USDS Joint Venture