[As of June 2020, Quora has become a “remote-first” company. This position can be performed remotely from multiple countries around the world. Please visit quora.com/eligible_countries for details regarding employment eligibility by country.]
The vast majority of human knowledge is still not on the internet. Most of it is trapped in the form of experience in people’s heads, or buried in books and papers that only experts can access. More than a billion people use the internet, yet only a tiny fraction contribute their knowledge to it. We want to democratize access to knowledge of all kinds — from politics to painting, cooking to coding, etymology to experiences — so if someone out there knows something, anyone else can learn it. Our mission is to share and grow the world’s knowledge, and we’re building a world-class team to help us achieve this mission.
About the Team:
Our small engineering team works on challenging problems every day. We have a culture that’s rooted in constantly learning and improving, 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. Our engineers focus on creating polished products and writing high-quality code by designing APIs and abstractions that are extensible and maintainable. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a significant impact on our product and our company.
About the Role:
We are looking for an experienced Machine Learning engineer to join our growing engineering team, working on recommendation systems such as feed, notifications, and Quora’s famous digest emails and A2A. At Quora, we use machine learning in almost every part of the product and recommendation systems play an important role in connecting users with content. As a recommendation systems expert, you will have a unique opportunity to have high impact by advancing our ranking systems as well as uncovering new opportunities to apply machine learning to the Quora product. You will also play a key role in developing tools and abstractions that our other developers will build on top of.
- Improve our existing machine learning systems using your core coding skills and ML knowledge.
- Identify new opportunities to apply machine learning to different parts of the Quora product.
- Work with other machine learning engineers to implement algorithms and systems efficiently.
- Take end-to-end ownership of machine learning systems – data pipelines, candidate extraction, feature engineering, model training, as well as integration into our production systems.
- Ability to be available for meetings and impromptu communication during Quora’s “coordination hours” (Mon-Fri: 9 am-3 pm Pacific Time). Learn why here
- 5+ years of professional software development experience in machine learning
- 3+ years of professional experience working on recommendation systems
- Good understanding of mathematical foundations of machine learning algorithms
- Previous experience building end-to-end machine learning systems.
- Good communication and interpersonal skills
- BS, MS, or PhD in Computer Science, Engineering, or a related technical field
- 2+ years of experience writing Python or C++ code
- Experience with leading large-scale multi-engineer projects
- Flexible and positive team player with outstanding interpersonal skills
- Passion for Quora’s mission and goals
For Colorado based applicants, the minimum salary range is $185,000 – $216,000 + equity + benefits. For California, New Jersey, and New York based applicants, the minimum salary range is $218,000 – $255,000 + equity + benefits. There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.
Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.