Machine Learning Engineer, Global Services Security – Office of Security Full-time

Amazon Web Services is looking for world class software developers with experience in machine learning to join the Security Innovation team in Global Services Security (GSS). AWS GSS is responsible for delivering product-led, people-powered services that help our customers operate their businesses securely on AWS, and we are accelerating our adoption of AI/ML. This is an exciting opportunity to contribute at the intersection of AI/ML, cloud, and cybersecurity. In this role, you are a passionate, talented, and inventive Software Development Engineer (SDE) with strong experience in ML, including areas such as generative AI, Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU). Your primary responsibility will be to develop AI/ML solutions to meet the needs of our customers. You will have the opportunity to work with other software developers, data scientists, and internal and external customers alike.

Key job responsibilities

* Work closely with product, engineering, and science teams to design, build, and deploy end-to-end machine learning solutions

* Optimize and scale machine learning models for production environments

* Implement data pipelines and infrastructure for model training and serving

* Collaborate with data scientists and software engineers to integrate ML solutions into applications

* Monitor and maintain deployed ML models and solutions

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

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.

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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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 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.

BASIC QUALIFICATIONS

– 3+ years of non-internship professional software development experience

– 3+ 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

– Experience with Python and frameworks such as Pytorch, TensorFlow

– 3+ years experience developing and deploying large-scale machine learning models and/or applications in production, including batch and real-time data processing, model containerization, CI/CD, REST or GraphQL APIs.

PREFERRED QUALIFICATIONS

– Bachelor’s degree in computer science or equivalent

– 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

– Hands-on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar. Prior experience training and fine-tuning Large Language Models (LLMs)

– Experience with serverless, event-driven architectures in AWS, including system design, development, and production operations; and infrastructure-as-code using AWS CDK, CloudFormation, or Terraform.

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.