Staff ML Engineer, Recommendation Systems (Remote)

Jobicy; United States; Remote; USD 220,000 - 321,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Remote work reimbursement

Equity refreshers

Paid time off

Employee assistance program

Job summary

Quora seeks a Staff Machine Learning Engineer to define the technical future of its home feed recommendation ecosystem. You will own the end-to-end recommender stack, including candidate generation, retrieval, ranking, re-ranking, and multi-objective optimization, and lead ML experiments that improve engagement.

You will deploy generative models at scale, mentor peers, and collaborate with product, data science, and infrastructure teams in a remote-first environment.

Qualifications

• 6+ years of professional software development experience in machine learning.
• 4+ years building and optimizing Home Feed recommendation systems for social media and UGC platforms.
• Deep knowledge of the full recommender stack: candidate generation, retrieval, ranking, re-ranking, embeddings, optimization.
• Experience leading large-scale ML projects end-to-end with measurable outcomes.
• Strong communication and collaboration skills.

Responsibilities

• Set the technical direction for Quora’s home feed recommendation systems.
• Lead high-impact projects across the recommender stack from generation to ranking and optimization.
• Drive measurable improvements in user engagement through online experiments.
• Own ML systems including data pipelines, feature engineering, training, and production integration.
• Mentor engineers and raise the bar for code quality and AI-assisted development.

Skills

Recommendation systems

Machine learning

Feed ranking

Information retrieval

Learning to rank

Feature engineering

Online experimentation

Python

C++

Generative AI

Education

BS/MS/PhD in Computer Science

Job description

Quora seeks a Staff Machine Learning Engineer to define the technical future of its home feed recommendation ecosystem. You will own the end-to-end recommender stack, including candidate generation, retrieval, ranking, re-ranking, and multi-objective optimization, and lead ML experiments that improve engagement.

You will deploy generative models at scale, mentor peers, and collaborate with product, data science, and infrastructure teams in a remote-first environment.