Job description

Who are we? RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC. Role Overview We are looking for a Head of Machine Learning to lead the development of the next generation of our machine learning platform. This role combines technical leadership, hands-on development, and organizational building. You will be responsible for the infrastructure for training and serving the deep learning models powering our Demand Side Platform. Our machine learning systems power real-time advertising use cases including bidding, ranking, pacing, and fraud detection. These models operate in extremely latency-sensitive environments, serving millions of predictions per second. You will work closely with engineering and product leadership to translate business challenges into scalable ML solutions. This role is ideal for someone who enjoys building systems and teams from scratch, moving quickly, and owning outcomes end-to-end. Key Responsibilities Design and build the next generation production ML system, including training pipelines, feature pipelines, and real-time inference services. Work directly in the codebase to prototype models, evaluate approaches, and ship production systems. Build and lead the machine learning team, including hiring, mentoring, and establishing engineering culture. Partner with engineering to design infrastructure capable of serving millions of low-latency predictions. Identify high-impact ML opportunities across bidding, ranking, pacing, fraud detection, and optimization. Establish best practices around experimentation, model evaluation, monitoring, and continuous improvement. Translate business and product goals into measurable machine learning improvements. Required Skills / Experience 7+ years of experience with a focus on building production machine learning systems. Experience taking ML models from research or prototype to production at scale. Strong programming background in Python and at least one systems language (C++, Java, Rust, or Go). Experience working with large-scale data pipelines and training infrastructure. Comfortable operating in early-stage environments where you may be both the architect and the implementer. Strong product intuition and ability to prioritize ML work based on business impact. Experience scaling ML teams. Excellent communication skills and ability to work across engineering, product, and leadership. Fluent Mandarin required. Nice-to-Have Experience in advertising technology and real-time systems. Experience operating ML infrastructure in on-prem environments using open-source tools including Spark, ClickHouse, AeroSpike, and Prefect. RZR is an equal opportunity employer RZR is a place where everyone can grow. However you identify, and whatever background you bring with you, we invite you to apply if this role excites you. RZR provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any kind. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Requirements

Must-haves

This role is ideal for someone who enjoys building systems and teams from scratch, moving quickly, and owning outcomes end-to-end.
Design and build the next generation production ML system, including training pipelines, feature pipelines, and real-time inference services.
Work directly in the codebase to prototype models, evaluate approaches, and ship production systems.
Build and lead the machine learning team, including hiring, mentoring, and establishing engineering culture.
Partner with engineering to design infrastructure capable of serving millions of low-latency predictions.
Identify high-impact ML opportunities across bidding, ranking, pacing, fraud detection, and optimization.
Establish best practices around experimentation, model evaluation, monitoring, and continuous improvement.
Translate business and product goals into measurable machine learning improvements.
Required Skills / Experience
7+ years of experience with a focus on building production machine learning systems.
Experience taking ML models from research or prototype to production at scale.
Strong programming background in Python and at least one systems language (C++, Java, Rust, or Go).
Experience working with large-scale data pipelines and training infrastructure.
Comfortable operating in early-stage environments where you may be both the architect and the implementer.
Strong product intuition and ability to prioritize ML work based on business impact.
Experience scaling ML teams.
Excellent communication skills and ability to work across engineering, product, and leadership.
Fluent Mandarin required.

Nice-to-haves

Experience in advertising technology and real-time systems.
Experience operating ML infrastructure in on-prem environments using open-source tools including Spark, ClickHouse, AeroSpike, and Prefect.
RZR is an equal opportunity employer
RZR is a place where everyone can grow. However you identify, and whatever background you bring with you, we invite you to apply if this role excites you.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpythonjavarustgo

Platform: greenhouse
Effort: quick