Who we are:
Cortex's purpose is to improve Twitter by enabling advanced and ethical AI.
Within Cortex, the ML Platform group focuses on accelerating the impact of ML through tools and infrastructure. All of Twitter’s major product initiatives, serving the public conversation, ensuring its health, and amplifying diversified revenue streams integrally rely on machine learning.
We are on a quest to improve productivity of ML practitioners by an order of magnitude within three years. Some of the key areas we focus on include large scale feature management, model training and serving, pipeline orchestration, notebook environments, data processing, observability, differential privacy analysis tools and ML experiment management.
We care deeply about
Staying abreast of and leveraging recent advances in machine learning.
Improving productivity and iteration speed of ML practitioners at Twitter.
Improving fairness and transparency of our AI systems.
Leveraging open source and off-the-shelf technologies while making deep investments in problems which are unique to Twitter.
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 a customer first mindset.
You take pride in polishing and supporting our products.
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 PhD in computer science
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. Having conducted research and published peer-reviewed articles in a Machine Learning field is a plus.
Track record of conceiving of significant innovations that result in substantial positive impact to customers.
Deep understanding of latest developments of ML systems, techniques, open source and cloud offerings
Experience with Recommender Systems, NLP or Graph Learning 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.