Software Engineer, Ads Measurement & Effectiveness

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) with match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Holidays & PTO

Job summary

TikTok Inc. is seeking a data-focused backend engineer for the Signals & Measurement team in San Jose, CA.

You will design scalable signal quality pipelines and cross-platform identity resolution, and own attribution modeling end-to-end to measure ad effectiveness. You will build large-scale experimentation infrastructure and real-time data pipelines, applying statistics and ML to advertiser data while collaborating with Product, Data Science, and Infra teams to deliver production systems

Qualifications

• BS/MS in Computer Science, Statistics, Mathematics, or a related field.
• Strong software engineering skills; proficient in Python, Go, Java, or C/C++.
• Solid foundation in data structures, algorithms, and system design.
• Experience building backend or data-intensive systems at scale.
• Foundational knowledge in statistics or machine learning.

Responsibilities

• Design and build signal quality frameworks, including anomaly detection and denoising at scale.
• Develop cross-platform identity resolution systems with probabilistic matching and graph algorithms.
• Own attribution model design and end-to-end implementation (MTA, modeled conversions).
• Build large-scale experimentation infra and real-time data pipelines for conversion lift and cross-media measures.
• Explore LLM-powered signal intelligence for classification and automated signal correction.
• Collaborate with Product, Data Science, and Infra teams to productionize algorithms for advertisers globally.

Skills

Python

Go

Java

C/C++

Statistics

Education

BS/MS in Computer Science/Statistics/Math

Job description

Responsibilities

The Signal & Measurement team at TikTok Ads is responsible for the full stack of advertising effectiveness - from signal collection and identity resolution to attribution modeling and causal measurement. We build the systems and models that help advertisers worldwide understand and maximize the true business value of their ad spend on TikTok.

Our work sits at the intersection of distributed systems and causal inference. We operate at massive scale while applying rigorous statistical methodology to answer the hardest question in advertising: "Did this ad actually work?"

What You'll Own

• Design and build signal quality frameworks - anomaly detection, signal recovery, denoising, and correction pipelines that ensure the reliability of advertiser conversion data at scale.
• Develop and optimize cross-platform identity resolution systems, improving the precision and coverage of our Identity Graph through probabilistic matching models and graph algorithms.
• Own attribution model design and implementation end-to-end, including multi-touch attribution (MTA), modeled conversions, and incrementality measurement.
• Build large-scale experimentation infrastructure and real-time data pipelines powering Conversion Lift, Brand Lift, Split Test, and cross-media measurement products.
• Explore LLM-powered signal intelligence - leverage large language models for semantic understanding of advertiser conversion data, enabling intelligent classification, quality assessment, and automated correction of event signals.
• Collaborate cross-functionally with Product, Data Science, and Infrastructure teams to translate algorithmic ideas into production systems serving advertisers globally.

Qualifications

Minimum Qualifications:

• BS/MS in Computer Science, Statistics, Mathematics, or a related field.
• Strong software engineering skills; proficient in at least one of: Python, Go, Java, C/C++.
• Solid foundation in data structures, algorithms, and system design.
• Experience building backend or data-intensive systems at scale.
• Foundational knowledge in statistics or machine learning - you should be comfortable with concepts like hypothesis testing, causal inference, regression, and probabilistic models.

Preferred Qualifications:

• Experience in one or more of the following areas:
• Signal processing: conversion data quality, anomaly detection, data imputation and denoising.
• Identity resolution: ID mapping, entity resolution, probabilistic matching, graph algorithms.
• Attribution modeling: last-click, MTA, incrementality, or conversion modeling.
• Experimentation: A/B testing, Lift Studies, or productionizing causal inference methods.
• Adjacent algorithm domains such as recommendation systems, search ranking, or computational advertising.
• Ability to independently drive the full lifecycle - from problem definition and model design to production deployment - rather than solely implementing specs written by others.
• Domain knowledge in ads tech and a genuine curiosity about how advertisers think about ROI and measurement.

Job Information

Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $316800 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.

• 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.