Staff Machine Learning Engineer, Recommendation Systems - Quora (Remote)

Description

The company is privately held and works remote-first, with roles that can be done from several countries. Eligible countries are listed on the company careers site.

The company runs a global knowledge-sharing platform with millions of monthly unique visitors. It also runs a cloud workspace where millions of users run several AI agents on shared context and tools, with one subscription covering every frontier model.

Machine learning shapes nearly every part of the product. The engineering team is lean and fast-moving, takes on hard, high-impact problems, and works with full autonomy and bold experimentation.

This role works on the company's main knowledge platform.

You will set the technical direction for feed ranking and retrieval, lead the largest modeling bets, and bring LLMs and generative models into how content is understood and ranked. You will also extend recommendations to notifications and digest emails, and build shared tools for the whole engineering organization.

This is a hands-on individual contributor role with company-wide scope. You will write production code, mentor people, and help shape how the team uses AI-assisted development to ship faster.

Responsibilities

• Set the technical direction for the home feed recommendation systems.
• Lead the most impactful work across the recommender stack, including candidate generation, retrieval, ranking, re-ranking, and multi-objective optimization.
• Improve engagement and content quality through carefully designed online experiments.
• Own ML systems end to end: data pipelines, candidate extraction, feature engineering, training, and production integration.
• Find new places to apply machine learning across the product.
• Work with product, data science, and infrastructure teams to agree on priorities and tradeoffs.
• Mentor engineers and set the standard for code quality, modeling rigor, and AI-assisted development speed.

Requirements

• Be available for meetings and quick conversations during the company's coordination hours, Monday to Friday, 9am to 3pm Pacific Time.
• Have 6+ years of professional software development experience in machine learning.
• Have 4+ years of professional experience building and tuning home feed recommendation systems for social media and user-generated content platforms.
• Know the full recommender stack well: candidate generation, retrieval, ranking, re-ranking, embeddings, and multi-objective optimization.
• Understand the mathematical foundations of machine learning algorithms in depth.
• Have led large-scale ML projects end to end with measurable outcomes.
• Communicate and work well with others.
• Hold a BS, MS, or PhD in Computer Science.
• Preferred: 6+ years of experience writing Python or C++.
• Preferred: hands-on experience deploying and running generative models at scale.
• Preferred: background in notifications, email or digest recommendations, or growth and lifecycle modeling.
• Preferred: flexible and positive team player.
• Preferred: publications at venues such as RecSys, KDD, NeurIPS, or ICML.
• Preferred: a passion for the company's mission and goals.

Conditions

Remote role, with hiring open across multiple countries. Eligibility depends on the country.

Applications are accepted on an ongoing basis, and this role backfills an existing vacancy.

Starting pay depends on experience, location, education, and business needs.

Applies to US candidates only: base salary range of $219,989 - $320,613 USD, plus equity and benefits.

Applies to Canadian candidates in Toronto and Vancouver: base salary range of $282,469 - $329,337 CAD, plus equity and benefits.

Applies to Canadian candidates in all other locations: base salary range of $263,638 - $307,381 CAD, plus equity and benefits.

In equity-eligible countries, part of equity compensation can be taken as cash through a flexible program.

AI tools may help sort applications and take interview notes, but team members make all decisions.

The company is an equal opportunity employer and does not discriminate on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Benefits

• Medical, dental, and vision coverage.
• Equity refreshers.
• Remote work reimbursement.
• Paid time off.
• Employee assistance programs.
• Other benefits, which vary by country.