Amazon Machine Learning Engineer AWS Training & Certification 

United States, Washington, Seattle 

440556905

Key job responsibilities
- Focus on Model Deployment, including all tasks necessary to turn a prototype into a production model, such as
o Model data pipelines: building data pipelines to produce inputs for training and inference in both online and offline contexts.
o Training and inference pipelines: orchestration of model training and inference jobs.
o Post-inference work: work required after the model’s output to serve business needs such as integration with engineering systems
- Design, develop, and maintain full-stack internet-scale web applications on AWS; heavy focus on RESTful APIs, infrastructure as code, and test automation
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Enhance observability and logging mechanisms to proactively identify and troubleshoot issues, and maintain dialogue state for offline training and model improvement
- Contribute to building an infrastructure that facilitates end-to-end ML workflows.
A day in the life
On-call ResponsibilityThis position involves on-call responsibilities, typically for one week every two months. We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault-tolerant. When we do get paged, we work together to resolve the root cause so that we don't get paged for the same issue twice.About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why AWS
Work/Life BalanceMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent