81 Event- Computer Vision , Amazon-Textract

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Are you interested in working on fascinating scientific and engineering challenges of modern AI? Would you like to contribute to the development of the future generation of cloud computing at Amazon Web Services?

As an Applied Scientist, you will be working on cutting edge research at the intersection of deep learning and causal inference. You will be part of an ambitious and multidisciplinary team of scientists and software engineers that is together developing novel tools to learn and exploit causal knowledge from real-world visual data.

The AWS Causal Representation Learning Lab is located at the Tübingen site in Germany. Our goal is to develop the next generation of AI algorithms by learning and exploiting causal invariances extracted from non-i.i.d. visual data. Going beyond mere correlations, we quantify the causes of observations and provide robust predictions. Our mission is to provide credible and reliable AI models that do not fail unexpectedly under distribution shifts. The successful applicant will have previous research experience with either representation learning or causality, with an interest in the other.

As an Applied Scientist in the Causal Representation Learning Lab, you will be responsible for: - Developing new machine learning and neural network architectures building on and inspired by causal principles

• Causal discovery in complex environments and large-scale visual datasets
• Benchmarks and data sets for causal representation learning
• Developing evaluation pipelines to test model performance under distribution shifts
• Engaging with product and development teams across AWS and Amazon to help bringing your scientific breakthroughs to customers
• Contribute to our unique multidisciplinary environment with your own creativity and talent
• Mentoring junior scientists and interns / PhD students

We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.

BASIC QUALIFICATIONS

• A PhD/M.Sc. in Computer Science, Mathematics, Physics, Statistics or any other field with strong quantitative focus
• Demonstrated research experience in either causality or representation learning with a proven track record of publications at well-regarded conferences and journals
• Strong software development skills
• Proven written and verbal communication skills in English

PREFERRED QUALIFICATIONS

• Relevant additional experience such as post-doctoral roles or industry research
• Experience with cloud computing products
• Expertise on a broad range of machine learning methods
• Excellent problem solving ability
• Fascination for conceptual problems raised by causal inference