Senior ML Engineer - Ranking & Recommendations (Remote)

Quora; Ireland; Remote; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Health benefits

Equity refreshers

Remote work reimbursement

Paid time off

Employee assistance program

Job summary

Quora is seeking an experienced machine learning engineer to join our distribution team, focusing on recommendation systems like feed, notifications, and digest emails. This role emphasizes impact across the Quora product with strong ownership of ML pipelines and model development.

You'll work in a remote-first environment with flexible hours, collaborating with fellow ML engineers to push state-of-the-art ranking models and apply ML to new product areas while maintaining production systems and

Qualifications

• 3+ years of professional experience working on recommendation or ranking models.
• Strong understanding of mathematical foundations of ML algorithms.
• Experience building end-to-end ML systems.
• BS, MS, or PhD in Computer Science, Engineering, or related field.

Responsibilities

• Improve our existing machine learning ranking models using core coding skills and ML knowledge.
• Take end-to-end ownership of ML systems—data pipelines, candidate extraction, feature engineering, model training, and production integration.
• Identify new opportunities to apply ML to different parts of the Quora product.
• Collaborate with other ML engineers to implement efficient algorithms and systems.

Skills

Python

C++

Machine Learning

Recommendation systems

Data pipelines

Education

BS/MS/PhD in CS or related field

Tools

PyTorch

TensorFlow

Job description

Quora is seeking an experienced machine learning engineer to join our distribution team, focusing on recommendation systems like feed, notifications, and digest emails. This role emphasizes impact across the Quora product with strong ownership of ML pipelines and model development.

You'll work in a remote-first environment with flexible hours, collaborating with fellow ML engineers to push state-of-the-art ranking models and apply ML to new product areas while maintaining production systems and