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Machine Learning Engineer, AWS Training

2 months ago


Seattle, United States Amazon Web Services (AWS) Full time

Minimum Qualifications:

  • 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

Shape the future of learning with us The AWS Training & Certification (T&C) team empowers millions of individuals and companies worldwide to cultivate and expand their professional skills using AWS products and services in the cloud. This job is a unique opportunity leveraging Generative AI to build the next generation of learning experiences for our customers.

Key Job Responsibilities:

  • Focus on Model Deployment, including all tasks necessary to turn a prototype into a production model, such as:
  • Model data pipelines: building data pipelines to produce inputs for training and inference in both online and offline contexts.
  • Training and inference pipelines: orchestration of model training and inference jobs.
  • 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: Are you passionate about building full-stack software tools and systems that solve critical business problems? Do you love collaborating with peers, UX-Designers, and Product Managers to build delightful experiences for our customers? If so, this is the team for you. Join us, and you will be part of a team that is focused on inventing and building solutions that will improve lives through learning.

This position involves on-call responsibilities, typically for one week every two months. We work to ensure that our systems are fault-tolerant. When we do get paged, we work together to resolve the root cause.

We are looking for highly motivated software development engineers to bring in their ideas and experience to deliver great products to our customers.

About the Team: 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.

Why AWS: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating.

Work/Life Balance: We value work-life harmony. Flexible work hours and arrangements are part of our culture.

Inclusive Team Culture: Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion.

Mentorship and Career Growth: We’re continuously raising our performance bar as we strive to become Earth’s Best Employer.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market.

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