Sr. Applied Scientist, Aws Ai/ml Automation
vor 2 Wochen
PhD degree with specialization Machine Learning/Deep Learning, Algorithms, Optimization, and related fields
- Experience with machine learning/deep learning frameworks (TensorFlow, PyTorch, MXNet, or similar) and related libraries
- Experience developing solutions on the cloud
- Experience mentoring and hiring more junior scientists
- Publication record at top conferences and in associated journals
Job summary
Interested in machine learning and AI? Can you envision a future where technology is driven primarily by smarter machines?
Key job responsibilities
- Understand customer needs and translate those into ML/AI-based solutions
- Develop novel ML solutions that are robust, practical, and scalable which lay the foundation for improvement of existing or the creation of new products
- Contribute to open source software and publish results in academic journals and at conferences
- Partner with engineering teams to transfer viable solutions into products
A day in the life
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.
About the team
The mission of AWS AI/ML is to make machine learning easy, fast, and universal across all of our customers. Our world class platform provides the services that runs 85% of all on-cloud machine learning through performance optimizations, machine learning tools, and SDKs to democratize machine learning. Our customers include scientists, data analysts, and ML engineers all building and deploying models through either SageMaker or self-managed instances on EC2/EKS.
If you are passionate about advances in deep neural networks, large-scale distributed training or federated learning, and have a proven track record of bringing innovative research to customers, we would like to talk with you.
- Non-academic experience in a professional setting such as an internship or full time employment position
- Proven experience partnering with software and engineering teams
- Proven written and verbal communication skills
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