Back to jobs

Senior Machine Learning Engineer, Ads - Quora (Remote)

Remote - Multiple Locations · United States · Ireland · Canada · & 13 other countries · United States

Live, first seen by us 51 days ago
Pay
Multiple pay statements — pay source
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.
Read the full posting
Work setting
Remote — work setting source
Location type: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering — team source
Department: Engineering
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status?
From the employer’s application form

What you’ll work on

Full posting
  • 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

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • 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

Preferred experience

  • 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
Qualification wording
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
Education & alternatives
- 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:

About Quora

Quora’s mission is to grow the world's collective intelligence.

In the employer’s words · Read in context · Company website ↗

Apply at Quora

Posting record

Report an error
Status in our records
Live
First seen by us
Sep 14, 202651 days ago
Recorded sightings
32
Last seen by us
Nov 4, 2026
Employer says posted
Sep 10, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Time since we first saw it

Day 51

Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

Quora is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring is picking up
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • PyTorch
  • TensorFlow
Where the posting names them
- 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

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Applying through Ashby

  • No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.

Already applied? Track this application

About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

[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 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.

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, 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.

Responsibilities:

  • 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

Minimum Requirements:

  • 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

Preferred Requirements:

  • 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.

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 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

#LI-JC1
#LI-REMOTE

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
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.
More source context
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.
Location & working pattern

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:
More source context
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.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.