Machine Learning Engineer, Generative AI Innovation Center, AWS

Amazon launched the Generative AI (GenAI) Innovation Center (GAIIC) in Jun 2023 to help AWS customers accelerate enterprise innovation and success with Generative AI ( Customers such as Highspot, Lonely Planet, Ryanair, and Twilio are engaging with the GAI Innovation Center to explore developing generative solutions.

GAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud.

As a Machine Learning Engineer in GAIIC, you are proficient in developing and deploying advanced ML models and pipelines to solve diverse customer problems using Gen AI.

You will be working alongside scientists with terabytes of text, images, and other types of data and develop Gen AI based solutions to solve real-world problems.

You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

Key job responsibilities

Our ML Engineers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base.

You’ll bring a passion for the intersection of software development with generative AI and machine learning. You’ll also :

• Solve complex technical problems, often ones not solved before, at every layer of the stack.
• Design, implement, test, deploy and maintain innovative ML solutions to transform service performance, durability, cost, and security.
• Build high-quality, highly available, always-on products.
• Research implementations that deliver the best possible experiences for customers.

A day in the life

As you design and code solutions to help our team drive efficiencies in ML architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also :

• Build high-impact ML solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business solutions with your technical input.
• Work in a startup-like development environment, where you’re always working on the most important stuff.

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the 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?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

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 that empower us to be proud of our differences.

Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & 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.

Work / Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture.

When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud."

Sales, Marketing and Global Services (SMGS)

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.

AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

We are open to hiring candidates to work out of one of the following locations :

Atlanta, GA, USA Austin, TX, USA Boston, MA, USA Chicago, IL, USA Herndon, VA, USA Houston, TX, USA Jersey City, NJ, USA New York, NY, USA Santa Clara, CA, USA Seattle, WA, USA

BASIC QUALIFICATIONS

• 3+ years of non-internship professional software development experience
• 3+ years of programming with at least one software programming language experience
• 3+ years of design or architecture (design patterns, reliability and scaling) of new and existing machine learning systems experience
• 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and / or systems into production, including batch and real time data processing, model containerization, CI / CD pipelines, API development, model training and productionizing ML models
• Experience using Python and frameworks such as Pytorch, Tensorflow

PREFERRED QUALIFICATIONS

• Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
• Experience in training and fine-tuning of Large Language Models (LLMs), or experience with inference optimization
• Master’s degree in computer science or equivalent
• Experiences related to AWS services such as Sagemaker, EMR, S3, DynamoDB and EC2
30+ days ago