Staff Machine Learning Engineer, Ads - Quora (Remote)

Reposted 5 Days Ago
4 Locations
In-Office or Remote
190K-321K Annually
Senior level
Artificial Intelligence • Consumer Web • Digital Media • Machine Learning • Software
Our mission is to grow the world's collective intelligence. Wwe're building a world-class team to help us achieve this.
The Role
As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.
Summary Generated by Built In

[Quora is a privately held, "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’s mission is to grow the world's collective intelligence. To do so, we have two platforms:

  • Quora: a global knowledge sharing platform with over 300M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.

  • Poe: a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including GPT-5.2, Claude Opus 4.5, Grok 4.1, Veo 3.1, Nano Banana Pro (Gemini 3 Pro Image), and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.

Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.

This role will be working on our Quora product.

About the Team and Role:

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, revenue and company.

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

  • 5+ 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

  • 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 working with CTR, CVR, auto-bidding and auction systems

  • Effective communicator with strong leadership skills

  • Passion for Quora's mission and goals

At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.

Additional Information:

We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy.

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.

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.

  • US candidates only: For US based applicants, the salary range is $189,507 - $320,613 USD + equity + benefits.

  • Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $248,526 - $336,370 CAD + equity + benefits. For all other locations in Canada, the salary range is $231,958 - $313,946 CAD + equity + benefits.

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.

AI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team.

To ensure a secure hiring process, all final candidates will undergo identity verification and a comprehensive background check prior to onboarding.

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

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Top Skills

Ad Targeting
Feature Engineering
Machine Learning
Python
Ranking Systems
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The Company
HQ: Mountain View, CA
240 Employees
Year Founded: 2009

What We Do

Quora’s mission is to grow the world's collective intelligence through two platforms: Quora, a global knowledge-sharing site with 300M+ monthly users, and Poe, a hub for exploring and building with cutting-edge AI models, serving millions of users worldwide.

These products are powered by passionate, collaborative teams across the globe. Our culture values transparency, idea-sharing, and experimentation, fostering growth and celebrating success through impactful work.

Why Work With Us

At Quora, you'll shape the future of knowledge sharing by building innovative products that combine human expertise and AI. Work on groundbreaking projects with industry leaders while enjoying a supportive, flexible culture that values individuality, fosters growth, and empowers you to make a real impact alongside brilliant peers.

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