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Machine Learning Research Engineer – Recommender System 277 views

Who They Are

At Twitter, they would like to connect people with the conversations, topics, and content that are most relevant to them, in real-time.

They are a community of Machine Learning Researchers and Engineers, working to drive Twitter’s research in recommender systems. They work as embedded researchers amongst product teams through a range of systems – e.g. timelines ranking, push notifications, email notifications, ads. They operate at scale whilst ensuring fair and ethical use of our models and data.

What You Will Do

Apply your research expertise to improve our ML-driven recommender system products, help them develop new solutions and unlock new directions, as well as analyze and optimize the systems. You’ll work closely with product teams and mentor them on best practices for modern ML, and keep the wider team informed on the state-of-the-art. In addition, you will be in a strategic position to influence future roadmaps for Twitter’s recommender system products.

Who You Are

You have a depth of knowledge in an ML-driven field – e.g. Probabilistic modeling, Reinforcement learning, Deep learning, etc and you are interested in applying your knowledge and skillset to one or more challenges of our product areas – e.g. media/content understanding, new item/user modeling, temporal modeling, model performance optimization. You are passionate about the way they develop state-of-the-art technologies and are excited by the application of theory to real-world problems. You keep up to date with the latest developments in the field and look for ways to apply them to your current work/role.

Requirements

Master, Post-graduate or Ph.D. in computer science, machine learning, information retrieval, recommendation systems, natural language processing, statistics, math, engineering, operations research, or other quantitative disciplines; or equivalent work experience

Good theoretical grounding in core machine learning concepts and techniques

Ability to perform comprehensive literature reviews and provide critical feedback on state-of-the-art solutions and how they may fit different operating constraints

Experience with a number of ML techniques and frameworks, e.g. data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, etc

Familiarity with one or more DL software frameworks such as Tensorflow, PyTorch

Nice To Haves

  • Experience with large-scale systems and data, e.g. Hadoop, distributed systems
  • Publications in top conferences such as ICLR, NIPS, ICML, RECSYS, CVPR, ICCV, ECCV, etc
  • Experience with one or more of the following:
  • Natural Language Processing
  • Recommender Systems
  • Model optimization
  • Prediction / Inference (e.g. Bayesian)
  • Online Learning
  • Reinforcement Learning

They are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. They do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.

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