Machine Learning Software Engineer - Media Understanding
Who we are
Twitter is the best place to stay informed about what’s happening, with videos, images, GIFs and Periscopes all forming an important part of this global conversation. We’re using machine learning to better classify and filter the huge volume of media content that is shared on Twitter and are looking for a Machine Learning Software Engineer to help us build the models that power these systems.
We are made up of talented people from all over the world, and from many different backgrounds. We work together in our beautiful Central London location to build products that reach every person on the planet. Often we’ll relax together too – perhaps sharing lunch or a coffee, talking about what we’re doing, listening to and learning from one another. You’ll be a part of a close-knit team, working in concert with a focused organisation comprised of other Engineers, Designers and Product Managers.
We’ll both challenge and support you to do the best work of your career. You’ll have the opportunity to have a truly global impact.
What you’ll do
You will work as an integral part of our Media Understanding team to develop and implement models, algorithms, and systems that can be applied at scale to Twitter data. Examples of the kind of work you might do include building deep neural networks for image and video classification, object detection, similarity modeling and representation learning. You’ll work with both engineers and data scientists on the team and elsewhere at Twitter to build models and deploy them on our real-time inference platform.
Who you are
You probably have:
- A strong interest and some experience in computer vision/machine learning. Exposure to deep learning, classification, object detection, pattern recognition, large-scale/high dimensional clustering.
- A passion for applying state-of-the art technology to solve real-world problems at a large scale.
- Knowledge of core CS concepts such as data structures, algorithms, and optimization.
- Good communication skills, a pragmatic approach to problem solving, and a strong quantitative background.
- Some experience with software engineering best practices (e.g., unit testing, code reviews, design documentation).
- An interest in large datasets and modern data processing systems like Hadoop, Spark, Hive, and Presto.
- An advanced degree (masters, PhD) in machine learning/computer vision or equivalent work experience.
- Strong software development experience (e.g., Python, Scala, Java, C++, etc.)
- Strong machine learning/data analysis experience (e.g., Python, R, Matlab, etc.)
- Familiarity with one or more Deep Learning frameworks (e.g., TensorFlow, Torch, etc.)
- Experience in machine learning, artificial intelligence, statistics, or related fields
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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