Website Amazon
Job Description:
In this role, you’ll be responsible for developing integrations with The Neuron SDK and frameworks such as TensorFlow, PyTorch, and MXNet. You’ll be planning and implementing new features, working with customers to create innovative solutions, and actively contributing to open source projects.
Job Responsibilities:
- Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life.
- We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.
- We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
- Our team is dedicated to supporting new members.
- We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.
- Our senior members enjoy one-on-one mentoring.
- We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Job Requirements:
- Masters or PhD in Computer Science, Deep Learning, Artificial Intelligence, Applied Math, or related field
- B.S. Computer Science or related technical field
- 3+ years of experience with deep learning frameworks: TensorFlow, PyTorch, and MXNet
- 5+ years of professional experience in software engineering: debugging, performance analysis, and test design
- Meets/exceeds Amazon’s functional/technical depth and complexity for this role
- Experience with distributed training for Deep learning and High Performance Computing
- Meets/exceeds Amazon’s leadership principles requirements for this role
- 5+ years of professional experience with one or more of the following programming languages: C, C++, Java, or Perl
Job Details:
Company: Amazon
Vacancy Type: Full Time
Job Location: Cupertino, CA, US
Application Deadline: N/A
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