Senior Software Engineer - Full Stack AI/ML

Amazon.com, Inc.
Redmond, WA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours

Tech stack

C (Programming Language) Java (Programming Language) JavaScript (Programming Language) Artificial Intelligence Data Analysis C Sharp (Programming Language) C++ (Programming Language) Static Program Analysis Continuous Integration DevOps Python (Programming Language) Machine Learning
+3 more
Reliability Engineering Infrastructure Automation Frameworks Information Technology

Requirements

in test maturity reviews, static analysis reviews, meetings, on-call rotations, and incident responses throughout product development and operations cycles. Provides deep business and technical expertise as required to resolve major incidents. Bachelor’s Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience with Artificial Intelligence (AI), Machine Learning (ML), risk assessment systems, or intelligent automation solutions. (Appropriate for the R2D and Automated Risk Assessment space. Experience with DevOps practices, continuous integration and continuous deployment (CI/CD), infrastructure as code, and service reliability engineering. Experience analyzing large datasets and translating insights into product or engineering improvements. Experience leading technical initiatives and influencing architecture, design, and engineering best practices across teams. Demonstrated ability to drive operational excellence through automation, scalability, reliability, and continuous improvement.

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