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Senior Machine Learning Engineer - Ads (Remote) - job 1 of 2

[Quora is a "remote-first" company. This position can be performed remotely from multiple countries around the world. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.]

About Quora:

Quora is on a quest to democratize access to knowledge of all kinds, empowering individuals to learn anything they desire. We’re a passionate group of unique individuals. We celebrate success and enable our people the space for personal growth, providing opportunities to do meaningful work that maximize their potential. Our culture is deeply rooted in our tenets of transparency, idea-sharing, and experimentation, which fuel collaboration and innovation. We take pride in engaging with a high-performing, global team – and that is why people love what they do here. We have taken up an ambitious mission: to share and grow the world’s knowledge and we are driven by our unwavering commitment to excellence. As we build a team of exceptional individuals who share our passion, we invite you to join us on this journey and create a positive change that makes a significant impact in the world.

About the Team:

Our Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora. The team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Engrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. Our engineers focus on creating polished products and writing high-quality code by designing APIs and abstractions that are extensible and maintainable. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a huge impact on our product and our company.

About the Role:

Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. Today, we're working on a broad range of areas to grow our ads product to drive more value to our users and advertisers. As a member of the Ads Machine Learning team, you will have a chance to work with a diverse and talented global team of engineers and collaborate closely with cross-functional partners to help advertisers reach their performance goals through next-generation targeting and bidding products and to build a stronger connection between Quora users and its business products.

Responsibilities:

  • Improve our existing machine learning systems using your core coding skills and ML knowledge

  • Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems

  • Apply state-of-the-art machine learning algorithms at scale and serving for next-generation targeting and bidding products that directly impact the company’s top line metrics

  • Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment

  • Work with product and business teams on new innovative features for ad targeting and bidding to optimize advertisement performance

  • Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers

Minimum Requirements:

  • Ability to be available for meetings and impromptu communication during Quora's "coordination hours" (Mon-Fri: 9am-3pm Pacific Time)

  • 3+ years of professional software development experience in machine learning

  • Previous experience working in Adtech, developing ad targeting/retrieval/recommender systems

  • Previous experience building large scale ranking/recommendation systems

  • Good understanding of mathematical foundations of machine learning algorithms

  • Highly proficient coding ability writing Python, C++ or Golang code

  • BS, MS or PhD in Computer Science, Engineering or a related technical field

Preferred Requirements:

  • Experience with leading large-scale multi-engineer projects

  • Experience in productized reinforcement learning

  • Experience with privacy-preserving modeling techniques

  • Flexible and positive team player with outstanding interpersonal skills

  • Passion for Quora's mission and goals

We value your unique perspective. Even if you don't meet all the requirements, we want to learn more about you. Every point of view can make an impact. Apply today!

Additional Information:

US candidates only: For Colorado based applicants, the minimum base salary range is $128,000 - $156,000 + equity + benefits. For California, New Jersey, New York, and Washington based applicants, the minimum salary range is $151,000 - $184,000 + equity + benefits.

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs. Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Applicant Privacy Notice: https://www.careers.quora.com/applicant-privacy-notice

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CEO of Quora, Inc.
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Quora is a world renowned question-and-answer platfrom and knowledge market headquartered in Mountain View, California. Since its foundation in 2010, Quora's website has been visited by 300 million users a month.

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DATE POSTED
April 14, 2023

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