Machine Learning Engineer, Amazon General Intelligence (AGI)

Amazon; Seattle (WA); On-site; USD 200,000 - 250,000; Full time

Job summary

Join a forward-thinking team at a leading tech giant as a Machine Learning Engineer, where you'll spearhead the development of innovative algorithms and modeling techniques for cutting-edge Generative AI applications. With a focus on multi-modal and multi-lingual Large Language Models, you'll leverage state-of-the-art hardware and massive data sources to create impactful products that enhance customer experiences. This role offers the opportunity to influence the future direction of Artificial General Intelligence, making it a thrilling challenge for tech enthusiasts eager to push boundaries in AI technology.

Qualifications

• 3+ years of professional software development experience.
• Experience in design patterns and system architecture.

Responsibilities

• Develop and maintain platforms for LLM development and deployment.
• Lead the development of algorithms for large model training.

Skills

Software Development

Machine Learning

Generative AI

Algorithm Development

Data Processing

Education

Bachelor's degree in Computer Science

Tools

AWS Trainium

NVIDIA GPUs

Job description

Machine Learning Engineer, Amazon General Intelligence (AGI)

Job ID: 2870545 | Amazon.com Services LLC

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Software Development Engineer (Sr. SDE)/Machine Learning Engineer (MLE) to play a pivotal role in the development of industry-leading multi-modal and multi-lingual Large Language Models (LLM). As our Sr. SDE/MLE superstar, you'll have the power to lead the charge in developing algorithms and modeling techniques that will push the boundaries of large model training using cutting-edge hardware like GPUs and AWS Trainium. Your groundbreaking work will directly impact our customers' lives through products and services powered by your Generative AI breakthroughs!

Key job responsibilities:

1. Ability to quickly learn cutting-edge technologies and algorithms in the field of Generative AI to participate in our journey to build the best LLMs.
2. Responsible for the development and maintenance of key platforms needed for developing, evaluating, and deploying LLM for real-world applications.
3. Work with other team members to investigate design approaches, prototype new technology, and evaluate technical feasibility.
4. Work closely with Applied scientists to process massive data, scale machine learning models while optimizing.

A day in the life:

As a SDE/MLE with the AGI team, you will be responsible for leading the development of novel algorithms and modeling techniques to advance the state of the art of large model training using hardware like NVIDIA GPUs. Your work will directly impact our customers in the form of products and services that make use of Generative AI innovations. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multi-modal Large Language Models (LLMs) and other Generative Artificial Intelligence (Gen AI) applications. As a key player in our team, you'll have a significant influence on our overall strategy, shaping the future direction of AGI at Amazon.

BASIC 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

PREFERRED QUALIFICATIONS

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

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.