As a critical role in Science’s success, we are looking to hire Deep Learning Scientists to join the team that develops and implements the algorithmic core of a series of exciting new projects in AIG’s global science team focused on solving complex business problems. As a Deep Learning Scientist you will work in a dynamic team that develops cutting edge machine learning methods for future AIG products. We are currently hiring Deep Learning scientists across following themes:
Deep Reinforcement Learning and Unsupervised Learning / Generative models.
Natural Language Processing (NLP).
Recurrent Neural Networks, Sequence Learning and Sequence Analysis (and NLG).
This is an exciting opportunity for those who want to enjoy state-of-the-art R&D and be challenged and grow as a Deep Learning Scientist; along the way this role will contribute to game-changing products for the multi-trillion-dollar insurance industry and use AIG’s (the world’s largest insurer by many metrics) global network to deliver impact and change.
Responsibilities and Performance Objectives:
Employ the best of Deep Learning research for solving business problems; disrupting the current practice in insurance.
Build and refine Deep Learning algorithms that can find “useful” patterns in large multi-modal data (particularly, images, text, conversations, and transactional data).
Provide the business with new product ideas, as well as data-driven apps, insights and strategies.
Engage, develop foster and lead partnerships to advance research efforts across cross-functional projects.
Design scientific solutions for mining large data sets, and employing cutting edge techniques to develop scalable prototypes with transformational potential and value.
For senior roles, lead, inspire and mentor junior scientists and research assistants (interns).
Communicate (both oral and written) with colleagues and stakeholders (both internal and external).
Both senior candidates (i.e., with years of post-doctoral and/or industrial experience) and junior candidates (i.e., recent PhD graduates) are welcome to apply; we have and will offer positions appropriate to expertise and level of experience.
The minimum required skills include:
A postgraduate (MSc/PhD/Post-doc) qualification in a numeric discipline such as Statistics, Machine Learning, Computer Science, Signal Processing etc.
Completion of one significant project (equivalent of a PhD research project, and/or a viable commercial product) in one or more of the hiring themes.
Scientific expertise, strong track record, and real-world experience in Deep Learning, especially with hands-on experience in hyper-parameter tuning and deep construction / distribution (e.g., architecture design in DNN/CNN/RNN, parameter initialization, activation, normalization, and optimization).
Strong background in machine learning and statistical modeling (e.g., classification, regression, and clustering).
Expertise in programming (e.g., Python and C++) and computing technologies (high-performance computing, e.g., CUDA).
Ability to use existing machine/deep learning libraries (e.g., TensorFlow, Torch, Theano, Caffe, and scikit-learn).
Highly experienced with the information technology aspects of data collection, organization, and integration.
Review, direct, guide, inspire the research of more junior scientists in the team (for senior candidates).
An ideal candidate (is not required to, but) may also have:
Track record in integrating machine learning with real-time computing (including mobile apps and front-end systems).
Experience in employing machine learning in a commercial setting – in collaboration with product development teams.
Publication record in (and willingness to represent AIG in) scientific conferences such as NIPS, CVPR, ICML, ICCV, ECCV, ICLR, and IJCV.
Broad knowledge of machine learning (including topics such as graph theory, hierarchical modeling, and Bayesian inference).
Practical experience of modern big-data computing ecosystems (e.g., Apache Spark).
Senior candidates should have proven ability to engage with business, formulate technical problems from business needs and craft solutions to shape business priorities
How to apply:
Please mention NLP People as a source when applying
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