We are Quantcast. A global Demand Side Platform (DSP) powered by AI. Rooted in our DNA is a strong foundation of measurement and consumer analytics, enabling us to empower marketers to reach audiences and achieve measurable advertising outcomes across the Open Web.
Since 2006, Quantcast has consistently set the industry standard by introducing groundbreaking initiatives such as the first measurement platform for digital publishers and the first AI-powered DSP. If you're prepared to be part of an enthusiastic team that crafts cutting-edge solutions, then Quantcast is the ideal place for you.
The Modeling team is responsible for Machine Learning (ML) systems at Quantcast. We build and maintain multiple ML products that price millions of bid requests per second in a real-time auction environment to maximize advertiser outcomes. For each bid our models predict age, gender, viewability, fraud, advertiser relevance and many more characteristics. Using NLP, clustering and LLMs we build topics in multiple languages to help our advertisers target customers interested in relevant content.
As a Sr. Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof of concepts, and build out scalable real-time production systems to tackle challenges the company faces.
ResponsibilitiesDesign, code, test, and debug ML applications and constantly improve large-scale global systems that respond to millions of real-time requests per second efficiently.Run Machine Learning experiments to test new modeling ideas.Write clean, efficient, and maintainable code using industry best practices.Collaborate closely with engineering teams, to deliver high-quality ML products. Participate in code reviews and provide constructive feedback to team members.Identify performance bottlenecks and optimize system components for enhanced scalability.Generate and review proposals for further research and development directions.Keep up to date with developments in machine learning outside the company.ExperienceFluency in Python, Java or similar programming languages.Strong skills in mathematics and statistics.Working knowledge of ML algorithms such as classification, control systems, optimization, clustering, LLMs or recommendation systems.An interest in distributed system and software design, concurrent algorithms, data structures, and software engineering.The expected base salary range for this role is $171,700 - $232,300.
Ultimately, in determining your offer, we will take into consideration your geographic location, relevant experience and expertise, and other job-related factors. Furthermore, full-time roles are eligible for a bonus, equity, and benefits (depending on your location) which include hybrid work, vacation, medical, dental, and vision insurance, and retirement plans. Please see our Careers page for additional information.
Founded in 2006 and headquartered in San Francisco, Quantcast has employees in 18 offices across 10 countries. We are committed to building an inclusive and diverse environment where everyone can be their authentic self. We work to ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Recognizing the importance of flexible work environments, Quantcast operates in a hybrid work model. This model gives employees the opportunity to work from home two days a week and work in the office for team collaboration for the remainder of the time. Our hybrid model may differ based on location or team, so please consult with your hiring manager for further information. All hybrid employees can also work remotely for two weeks each year or, if eligible, apply for our fully remote work program. We strongly encourage vaccination for all Quantcast employees as a way to stop the spread of COVID and protect yourself and others.
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