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Senior Machine Learning Engineer, Ranking - Quora (Remote)

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

Live, first seen by us 24 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.
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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
  • Improve existing machine learning ranking models for feed and digest

  • Own end-to-end ML systems, from data pipelines to production integration

  • Find new places to apply machine learning across the Quora product

  • Implement algorithms and systems with other ML engineers

From the employer’s posting
Improve our existing machine learning ranking models using your core coding skills and ML knowledge
Take end-to-end ownership of machine learning systems - data pipelines, candidate extraction, feature engineering, model training, as well as integration into our production systems
Identify new opportunities to apply machine learning to different parts of the Quora product
Work with other machine learning engineers to implement algorithms and systems efficiently

What you’ll bring

All qualifications

Core experience

  • 3+ years of professional experience working on recommendation or ranking models
  • Good communication and interpersonal skills
  • Good understanding of mathematical foundations of machine learning algorithms

Preferred experience

  • 5+ years of experience writing Python or C++ code
  • Experience with generative recommendation systems
  • Experience with user behavior or user sequence modeling, transformers, or long sequence modeling applied to ranking
  • Experience with leading large-scale multi-engineer projects
Qualification wording
3+ years of professional experience working on recommendation or ranking models
Good communication and interpersonal skills
Good understanding of mathematical foundations of machine learning algorithms
5+ years of experience writing Python or C++ code
Experience with generative recommendation systems
Experience with user behavior or user sequence modeling, transformers, or long sequence modeling applied to ranking
Experience with leading large-scale multi-engineer projects
Education & alternatives
- Good communication and interpersonal skills - 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

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Status in our records
Live
First seen by us
Oct 11, 202624 days ago
Recorded sightings
23
Last seen by us
Nov 4, 2026
Employer says posted
Oct 8, 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 24

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

From 4,331 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

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  • C++
  • Python
Where the posting names them
Preferred Requirements: - 5+ years of experience writing Python or C++ code - Experience with generative recommendation systems

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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 small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a significant impact on our product and our company. We are looking for an experienced machine learning engineer to join our distribution team, working on recommendation systems such as feed, notifications, and Quora's famous digest emails. At Quora, we use machine learning in almost every part of the product and recommendation systems play an important role in connecting users with content.

As a ranking modeling expert, you will own and advance the second-phase ranking model behind feed and digest, one of the highest-leverage surfaces at Quora, by applying the latest machine learning techniques. You will also play a key role in developing methodologies that our other developers will build on top of.

Responsibilities:

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

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

  • Identify new opportunities to apply machine learning to different parts of the Quora product

  • Work with other machine learning engineers to implement algorithms and systems efficiently

Minimum Requirements:

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

  • 3+ years of professional experience working on recommendation or ranking models

  • Good understanding of mathematical foundations of machine learning algorithms

  • Previous experience building end-to-end machine learning systems

  • Good communication and interpersonal skills

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

Preferred Requirements:

  • 5+ years of experience writing Python or C++ code

  • Experience with generative recommendation systems

  • Experience with user behavior or user sequence modeling, transformers, or long sequence modeling applied to ranking

  • Experience with leading large-scale multi-engineer projects

  • Flexible and positive team player with outstanding interpersonal 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

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#LI-REMOTE

Source details

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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
About the Team and Role: Our small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a significant impact on our product and our company. We are looking for an experienced machine learning engineer to join our distribution team, working on recommendation systems such as feed, notifications, and Quora's famous digest emails. At Quora, we use machine learning in almost every part of the product and recommendation systems play an important role in connecting users with content. As a ranking modeling expert, you will own and advance the second-phase ranking model behind feed and digest, one of the highest-leverage surfaces at Quora, by applying the latest machine learning techniques. You will also play a key role in developing methodologies that our other developers will build on top of.

More relevant text appears in the full description.

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