Senior Machine Learning Engineer

Who you are

• Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
• 4+ years of professional software development experience in machine learning
• Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements
• Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes
• Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions
• Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow
• Good understanding of mathematical foundations of machine learning algorithms
• Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python
• BS, MS or PhD in Computer Science, Engineering or a related technical field
• Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning
• Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes
• Experience with leading large-scale multi-engineer projects
• Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies
• Experience with generative recommender systems
• Effective communicator with strong leadership skills
• Passion for Quora's mission and goals
• 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

What the job involves

• This role will be working on our Quora product
• Our Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas
• Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company
• Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist
• You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences
• This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line
• Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
• Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems
• Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints
• Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment
• Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance
• Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers

The application process

• We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy