Machine Learning Engineer II, Special Projects
Amazon
Seattle, Washington
Posted 1 months ago
Responsibilities
Primary Duties
- Ability to quickly learn state of the art technologies and algorithms in the field of Generative AI to participate in our journey to build the best LLMs.
- Responsible for the development and maintenance of key platforms needed for developing, evaluating and deploying LLM for real-world applications.
- Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.
- Work closely with Applied scientists to process massive data, scale machine learning models while optimizing.
- Experience in distributed model training.
Full Job Description
Innovators Wanted
Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company's Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you're interested in innovating at scale to address big challenges in the world, this is the team for you.
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
Key Job Responsibilities:
Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company's Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you're interested in innovating at scale to address big challenges in the world, this is the team for you.
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
Key Job Responsibilities:
- Ability to quickly learn state of the art technologies and algorithms in the field of Generative AI to participate in our journey to build the best LLMs.
- Responsible for the development and maintenance of key platforms needed for developing, evaluating and deploying LLM for real-world applications.
- Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.
- Work closely with Applied scientists to process massive data, scale machine learning models while optimizing.
- Experience in distributed model training.
How to Apply
$103
/ hour
Amazon pays $103 for Data Scientist in Seattle, Washington, with most salaries ranging from $78 to $141. Pay can vary based on role, experience, and local cost of living.
Median
$103
Low
$78
High
$141
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Figures represent approximate ranges and may vary based on experience, location, and other factors. For the most accurate information, please consult the employer directly. Contact us to suggest updates to this information.





