Machine Learning Engineer (NLP) - Content Understanding & Applied Deep Learning
Twitter's Consumer Product Teams are responsible for core features of Twitter, which include Timelines, Tweets, Search, Trends, Recommendations, Notifications, and more! Our code operates at massive scale and speed, serving billions of requests per day, connecting hundreds of millions of active Twitter users to what’s happening.
Who We Are:
At Twitter, our mission is to instantly connect users to the information most meaningful to them. Content understanding team empowers various consumer product teams with signals derived with innovative machine learning technologies at the intersection of Natural Language Processing and Deep Learning. Our current work is focused around entities and how they are linked to each other and the ever changing world, a challenging task at Twitter’s scale.
Who You Are:
- You have a passion for Deep Learning and Natural Language Processing.
- You are excited about joining a team at the intersection of Applied Deep Learning, NLP and product.
- You stay up to date with the state of the art NLP research yet constantly look for ways to leverage ideas from the cutting edge advancements for product and business impact.
- You have good communication skills, a pragmatic approach to problem solving, and a strong quantitative background.
- You are a team player.
What You'll Do:
- You will develop Deep Learning models for content understanding and fundamental NLP problems such as entity recognition and linking.
- You will participate in the engineering life-cycle at Twitter, including writing ML modeling code and conducting code reviews.
- You will work alongside our product engineering, infrastructure and reliability teams to integrate your models with Twitter’s serving, cloud and data infrastructure.
- You will devise metrics and evaluation processes for the performance and impact of your models.
- MS or PhD in machine learning with a focus in NLP or equivalent work experience in the field.
- Experience with software engineering best practices (e.g., unit testing, code reviews, design documentation).
- Knowledge of core CS concepts such as data structures, algorithms, and optimization
- Familiarity with one or more Deep Learning frameworks (e.g., TensorFlow, Torch, etc.)
- Experience with large scale machine learning pipelines and relevance infrastructure.
- Experience with large datasets and modern data processing systems like Hadoop, Spark, Hive, and Presto.
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any 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.
After you apply, a recruiter may reach out to you for an introductory call.
If your background is a match for the role, you may phone interview with 1-2 people.
If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.
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