Sr. Machine Learning Engineer
Amazon Studios
Culver City, CAThis was removed by the employer on 9/14/2021 6:33:00 PM PST
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Full Time Job
Do you want to join Amazon Studios AI team – the team that is at the forefront of inventing new visual media technologies to provide incredible experiences to audiences around the world? Do you want to partner in building cutting-edge AI applications that most people cannot yet imagine?
If your answers to these questions are ''yes'', then come and join us at Amazon Studios AI, that is leveraging the latest breakthroughs in artificial intelligence to create a new way of watching video content. We expect our solution to disrupt the media and entertainment industry and delight audiences around the world. We are looking for talented and ambitious teammates who will Think Big with us. If you have a passion for groundbreaking technology, please join us and be part of this exciting, newly funded and fast-growing project.
On our team, you will partner with top AI scientists, software engineers, product managers, and others. You will be joining on the ground floor and will grow with our team all the way through to our expected launch. You will be expected to:
• Build cutting-edge AI powered applications that would define the future of media and entertainment industry.
• Invent with us to delight audiences around the world.
• Develop and maintain data pipelines and APIs
• Collaborate on end-to-end design and technical strategy.
• Will work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.
• Work in a collaborative environment with other engineers, scientists, product managers and others.
• Mentor and coach junior engineers in the team
Qualifications
• 4 years of professional software development experience
• 3 years of programming experience with at least one modern language such as Java, C , or C# including object-oriented design
• 2 years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems