Principal ML Engineer - Discovery
- San Francisco, CA, USA
- Employees can work remotely
Stay informed teams are responsible for all the product-focused machine learning and core product surface areas of Twitter.
Discovery is committed to building geographically distributed teams and we welcome applicants across the US/Canada to apply.
Within Stay Informed, the Discovery teams are dedicated to getting the majority of the world to converse in public using Twitter. We are composed of many teams across the company, including Product, Engineering, Design, and Research. These teams are responsible for understanding the needs of new users and users who are not very active and help them discover the value of Twitter by building personalized products.
This mission is to instantly connect people with conversations and audiences most meaningful to them. Realizing this goal involves work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems.
What You’ll Do
- Leadership: You will forge close relationships with the Principal and Staff engineering community as well as with engineering and product management leaders in multiple organizations at Twitter and you will partner with them to deliver impact. You will help define the vision and strategy for the organization and have substantial impact on the vision and strategy of customer and partner organizations.
- Planning and Execution: Plan and deliver projects that impact multiple organizations.
- Innovation: Identify opportunities for technological differentiation, investment or divestment. Ensure our organization’s work is aligned with broader company objectives.
- Mentorship: Provide mentorship and guidance to senior technical leaders and managers
- Technical: Spend time working on handson technical problems including design and implementation.
- Cross functional partnership: Work closely with leaders and organizations across the company to deliver impactful projects which may involve multiple disciplines.
Who You Are:
- A hands-on machine learning software engineer with a passion for working on deep infrastructure issues in ML environments.
- You thrive on working in concert with other smart people, including from distributed offices.
- You communicate fluidly, at the level of your audience, and seek to understand and be understood.
- You have an impact first mindset.
- You take pride in identifying and solving the big technical challenges of the organization.
- You understand how to prioritize and drive the most impactful backend infrastructure work given a company's mission and purpose.
- You have the ability to take on complex problems, learn quickly, iterate, and persist towards a good solution.
- You invest in the learning and growth of the people you lead.
- Senior-level experience and MS or Ph.D. in computer science or related fields.
- 10+ years of industry experience as a hands-on expert-level practitioner of machine learning.
- 5+ years of experience leading large ML initiatives across cross-functional teams in multiple organizations.
- Track record of building and maintaining large-scale machine learning systems in production.
- Track record of conceiving of significant innovations that result in substantial positive impact to customers.
- Deep understanding of the latest developments of ML systems, techniques, open-source and cloud offerings. Having experience with GCP ML tech stack is a plus.
- Experience with Recommender Systems is highly desirable.
- Fluent in one or more object-oriented languages like Java, Scala, C++, C#
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran, genetic information, marital status or any other legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.