Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Staff Machine Learning Engineer, Recommendation Systems – Quora
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- Salary
- USD 219,989–320,613 / yr
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Senior
- Published
- Apply before
- 26 Nov 2026
- Listing views
- 31
- Application actions
- 1
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The role, at a glance.
Quora seeks a Staff Machine Learning Engineer to set technical direction for its home-feed recommendation ecosystem. The role owns the full recommender lifecycle, including candidate generation, retrieval, ranking, re-ranking, feature engineering, model training, and production integration. This hands-on individual contributor will lead high-impact experiments, improve engagement and content quality, and extend recommendations to notifications and digest emails. The engineer will also deploy generative models at scale, mentor peers, and partner closely with product, data science, and infrastructure teams in a remote-first environment.
Role DNA
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Pace & Pressure
5/5Autonomy Level
5/5Communication Load
4/5Salary analysis
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Core skills
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Sample interview questions
I would first validate instrumentation, traffic allocation, and experiment integrity. I would segment results by user cohort, content type, and surface, then compare upstream retrieval coverage, ranking scores, latency, and downstream engagement metrics. Based on the findings, I would determine whether to roll back, adjust objectives, or run targeted follow-up experiments.
I would model the problem as multi-objective optimization, combining core engagement predictions with calibrated constraints or re-ranking objectives for diversity, freshness, and quality. I would define guardrail metrics, evaluate offline by segment, and validate tradeoffs through controlled online experiments.
I would begin by measuring recall and marginal value from each existing candidate source. I would add complementary retrieval channels such as embedding-based nearest-neighbor retrieval, graph signals, behavioral co-engagement, and freshness-oriented candidates, then deduplicate and optimize the blend based on incremental online impact and serving cost.
The system needs clear product objectives, robust offline and online evaluation, latency and cost controls, safety filtering, observability, and fallback behavior. I would also establish versioning, prompt or model governance, bias and quality monitoring, and an experimentation framework before expanding traffic.
I would set technical standards through design reviews, pairing, clear written proposals, and reusable tooling rather than becoming a bottleneck. I would delegate meaningful ownership, give specific feedback tied to outcomes, and reserve my direct implementation time for the highest-leverage architectural or modeling challenges.
About this role.
[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:
At Quora, machine learning drives nearly every aspect of our product, and our lean, high-velocity engineering team tackles complex, high-impact challenges daily. We thrive in a remote-first culture built on absolute autonomy, continuous learning, and bold experimentation.
We are looking for a Staff Machine Learning Engineer to define the technical future of Quora’s recommendation ecosystem. In this role, you will own the technical direction for feed ranking and retrieval, lead our highest-impact modeling bets, and pioneer the integration of LLMs and generative models to redefine how we understand and rank content. Beyond the home feed, you will also scale recommendation surfaces like notifications and digest emails, while architecting the underlying tools and abstractions that empower our entire engineering organization.
This is a high-leverage, hands-on IC role with organization-wide scope. You will write production code, mentor rising talent, and actively shape how our team leverages AI-assisted development to accelerate our shipping velocity.
Responsibilities:
Set the technical direction for Quora’s home feed recommendation systems
Lead the highest-impact projects across the recommender stack, from candidate generation and retrieval to ranking, re-ranking, and multi-objective optimization
Drive measurable improvements in user engagement and content quality through well-designed online experiments
Take end-to-end ownership of ML systems, including data pipelines, candidate extraction, feature engineering, model training, and production integration
Identify new opportunities to apply machine learning to different parts of the Quora product
Partner with product, data science, and infrastructure teams to align on priorities and tradeoffs
Mentor engineers and lead by example, raising the bar for code quality, modeling rigor and AI assisted dev velocity
Minimum Requirements:
Availability for meetings and impromptu communication during Quora’s “coordination hours” (Mon-Fri: 9am-3pm Pacific Time)
6+ years of professional software development experience in machine learning
4+ years of professional experience building and optimizing Home Feed recommendation systems for social media and user-generated content platforms.
Deep knowledge of the full recommender stack: candidate generation, retrieval, ranking, re-ranking, embeddings, and multi-objective optimization.
Deep understanding of mathematical foundations of machine learning algorithms
Experience leading large-scale ML projects end-to-end with measurable outcome
Strong communication and interpersonal skills
BS, MS, or PhD in Computer Science
Preferred Requirements:
6+ years of experience writing Python or C++ code
Hands-on experience deploying and running generative models at scale
Background in notifications, email/digest recommendations, or growth and lifecycle modeling
Flexible and positive team player
Publications at venues like RecSys, KDD, NeurIPS, or ICML.
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 $219,989 – $320,613 USD + equity + benefits.
Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $282,469 – $329,337 CAD + equity + benefits. For all other locations in Canada, the salary range is $263,638 – $307,381 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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