Senior Machine Learning Engineer, Ads - Quora (Remote)
Quora · Remote · Remote - Multiple Locations · United States · Ireland · Canada · & 13 other countries ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior level role
- Fully remote worldwide
- Ads ranking focus
- PyTorch or TensorFlow
- Pacific Time overlap
Join Quora's Monetization team to optimize advertising products through advanced machine learning. You will work on ads targeting, ranking, auction dynamics, and quality measurement, directly impacting revenue and user experience.
As an ads ranking specialist, you will improve CTR and CVR predictions, model calibration, and user-sequence modeling. The team operates with high autonomy, allowing you to own problems from research and data to deployment and maintenance.
What you'll do
- Develop and improve ads ranking models including prediction objectives and feature interactions
- Own end-to-end ML systems from data pipelines and feature engineering to production integration
- Apply deep learning advances to improve ranking within latency and cost constraints
- Collaborate with platform engineers to build scalable and efficient ML systems
- Partner with product and data teams to define objectives and design A/B experiments
- Identify new opportunities to apply ML across the Ads product to drive value
What you'll need
- Available for coordination hours Monday to Friday 9am-3pm Pacific Time
- 4+ years of professional software development experience in machine learning
- Experience deploying ads ranking models at scale with CTR or CVR prediction
- Proficient in evaluating ranking models via offline analysis and online experiments
- Experience using AI-assisted development tools for coding and debugging
- Hands-on experience building deep learning models with PyTorch or TensorFlow
- Strong Python programming skills for writing maintainable production ML code
- BS, MS or PhD in Computer Science, Engineering or a related technical field
Nice to have
- Experience with modern ranking architectures like attention-based user-sequence models
- Understanding of how ranking predictions interact with bidding and auctions
- Experience leading large-scale multi-engineer projects
- Experience addressing challenges like sparse labels or training-serving inconsistencies
- Experience with generative recommender systems
- Effective communication and strong leadership skills
Stack
- Python
- PyTorch
- TensorFlow
How you'll work
- Fully remote position eligible in multiple countries
- Requires availability during Pacific Time coordination hours
- High degree of flexibility and autonomy in engineering tasks
What you get
- Medical, dental, and vision coverage
- Equity refreshers and flexible equity program
- Remote work reimbursement
- Paid time off
- Employee assistance programs