Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Remote - Multiple Locations · United States · Ireland · Canada · & 13 other countries · United States
Live, first seen by us 51 days agoThere are many factors that will determine the starting compensation, including but not limited to experience, location, education, and business needs. US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits.
US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits. In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash.Read the full posting
Location type: RemoteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: EngineeringFrom the employer’s posting
Will you now or in the future require sponsorship for employment visa status?From the employer’s application form
Develop and improve ads ranking models, including CTR and CVR prediction and calibration
Own ML systems end to end, from data pipelines and training data to production integration
Apply deep learning and recommendation advances within production latency and cost limits
Design A/B experiments and measure advertiser performance and revenue gains
Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems
Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints
Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance
4+ years of professional software development experience in machine learning
Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements
Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes
Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions
Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow
Good understanding of mathematical foundations of machine learning algorithms
Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning
Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes
Experience with leading large-scale multi-engineer projects
Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies
- Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python - BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements:
Quora’s mission is to grow the world's collective intelligence.
In the employer’s words · Read in context · Company website ↗
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$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Day 51
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From 4,301 similar postings that came down. Coming down is not always a hire.
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- Good understanding of mathematical foundations of machine learning algorithms - Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python - BS, MS or PhD in Computer Science, Engineering or a related technical field
- Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions - Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow - Good understanding of mathematical foundations of machine learning algorithms
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
[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.]
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 millions of 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 cloud workspace where millions of users run multiple AI agents on shared context and tools. One subscription, every frontier model, and the collaboration layer that makes them work together.
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.
Our Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained 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. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and 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. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line.
Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems
Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints
Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment
Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance
Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers
Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
4+ years of professional software development experience in machine learning
Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements
Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes
Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions
Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow
Good understanding of mathematical foundations of machine learning algorithms
Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python
BS, MS or PhD in Computer Science, Engineering or a related technical field
Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning
Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes
Experience with leading large-scale multi-engineer projects
Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies
Experience with generative recommender 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.
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 compensation, including but not limited to experience, location, education, and business needs.
US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits.
Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits.
In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash.
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://careers.quora.com/quora-global-job-applicant-privacy-notice
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Selected passages from the saved posting. Check the full description for conditions and exceptions.
There are many factors that will determine the starting compensation, including but not limited to experience, location, education, and business needs. US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits.
US candidates only: For US based applicants, the salary range is $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 CAD + equity + benefits. In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash.
United States
[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:
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 compensation, including but not limited to experience, location, education, and business needs.
More relevant text appears in the full description.
No clear work-authorization passage found. Eligibility is unconfirmed.