Senior Machine Learning Engineer (Mandarin speaking)

About Moloco: Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy. Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue-generating ad businesses that balance user experience and advertiser performance. Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin. Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now! The Impact You’ll Be Contributing to Moloco: As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform. The Opportunity: Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results Mentor engineers on best practices for ML experimentation, productionization, and scaling Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals How Do I Know if the Role is Right For Me? You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus) You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes You value collaboration, accountability, and building systems that scale across teams and markets Compensation & Benefits U.S.-based employees have access to medical, dental, and vision insurance, a 401(k) plan with company match, short-term and long-term disability coverage, basic life insurance, and well-being benefits and perks. U.S.-based employees also receive up to 12 scheduled paid holidays per calendar year and one Thrive Day off per quarter. Additionally, all employees have Flexible Time Off (FTO). The successful candidate may be eligible for a bonus and equity awards. Eligibility and amounts are determined by performance and the terms of the applicable plans. The location for this role is listed above. For base pay range purposes, location-based compensation is grouped into the following regions. Your region is determined by your assigned work location. Region A: Menlo Park Office, New York Office, SF Bay Area, New York Metro Area Region B:  Seattle Office, Seattle, Los Angeles/Orange County, San Diego, Austin, Boston, Washington DC Metro Area, Miami Region C: All other U.S. locations Salary Ranges: