Machine Learning Researcher - Applied Machine Learning & Modeling
Join Twitter London’s Machine Learning community (Including Magic Pony) and help to transform the way Twitter applies Machine Learning.
Who we are:
We are a community of Machine Learning Researchers and Engineers, working to improve Twitter through applications of ML through a range of systems - e.g. recommendations, safety, abuse, ads. We operate at scale whilst ensuring fair and ethical use of our models and data.
We work as embedded researchers amongst product teams, looking to apply the expertise of the individuals to improve our products and unlock new capabilities.
What you will do:
Apply your research expertise to either improve existing solutions, unlock new directions or provide entirely new solutions within Twitter.
Who you are:
You’re a machine learning researcher with interests in a range of applications which could stem from media understanding to recommendation systems. You are passionate about the way we develop state-of-the-art technologies and apply them to products. You keep up to date with the latest developments in the field and look for ways to apply them to your current work/role.
- Post-graduate or PhD in computer science, machine learning, information retrieval, recommendation systems, natural language processing, statistics, math, engineering, operations research, or other quantitative discipline; 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 to 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
- Experience with one or more of the following:
- Approximate / k Nearest Neighbour theory, algorithms and frameworks
- Recommendation Systems
- Model optimisation - both training and runtime
- Online Learning
- Reinforcement Learning
- Publications in top conferences such as ICLR, NIPS, ICML, CVPR, ICCV, ECCV, etc
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.
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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