Machine Learning Engineer - Ads Prediction (Revenue Science)
Who we are:
In Twitter, we serve billions of advertising impressions and generate millions of dollars in revenue per day. Behind every ad, our ads ranking team, which operates one of the largest ML services at Twitter, evaluates at least thousands of candidates behind the scene. Our mission is to make Twitter ads as relevant in the moment as organic content on Twitter.
What you will do:
In order to realize our mission, we need your help to design and build state-of-the-art machine learning models and large-scale systems to predict users’ engagement/conversion on different ads as accurately as possible. Although you will work on cutting-edge problems, this position is not a research position. You will participate in the engineering life-cycle at Twitter, including writing production code, conducting code reviews and working alongside our infrastructure teams. You will be equally comfortable doing incremental quality work (e.g. feature engineering and model optimization) and also building brand new systems (e.g. parameter server) to enable future quality improvements.
- Apply machine learning and data mining techniques for a variety of modeling and relevance problems involving users, their tweets, their interests, twitter ads, relationship among entities.
- Work with large unstructured and structured data sets (multi-terabyte+, 100MM+ daily transaction volumes).
- Design and evaluate novel approaches for handling high-volume real-time data streams.
- Code using primarily Java and Scala; Map-Reduce frameworks such as Pig and Scalding; and scripting languages such as Python.
- Conduct design and code reviews.
- Conduct online A/B testing, interpret and understand algorithm performance.
Who you are:
You’re an applied data scientist or machine-learning engineer who wants to work on exciting algorithmic and deep infrastructure issues. If challenges like the Netflix prize, KDD cup and Kaggle excite you, this is your dream job.
- 2+ years industry experience with a Bachelors, MS or PhD in computer science, data mining, machine learning, information retrieval, recommendation systems, math, engineering, operations research, or other quantitative discipline; or equivalent work experience
- Fluent in one or more object oriented languages like Java, Scala, C#, C++
- Experience with Hadoop, Pig or other MapReduce-based architectures
- Knowledgeable of core CS concepts such as: common data structures and algorithms.
- Comfortable conducting design and code reviews.
- Experienced in operating Linux-based systems.
- Passionate about working with large unstructured and structured data sets
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.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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