Description

Amazon Web Services is looking for world class scientists to join the Security Innovation team in AWS Global Services Security (GSS). GSS is responsible for delivering product-led, people-powered services that help our customers operate their business 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. Your primary responsibility will be to envision, experiment, prototype, and mature to scale AI/ML solutions in our products to meet the needs of our customers. You will have the opportunity to work with multiple lines of business, and learn from (and contribute to) a variety of security use cases. This is a hands-on role where success is measured by producing solutions that have measurable impact. If you have experience with large scale machine learning and have a passion for security, this will be an exciting opportunity.

Key job responsibilities

• Collaborate with security and business teams to identify viable ML opportunities and develop a plan from experiments to proof-of-concept to software product.

• Conduct cutting-edge research and deliver new initiatives with potential to impact multiple teams and customers in the medium to long term.

• Invent, implement, and deploy state-of-the-art machine learning algorithms and systems for information security applications.

• Lead collaboration with software engineering teams to integrate successful experiments into large-scale, highly complex production services.

• Experiment and report results in a scientifically rigorous way.

• Advance the state of the art through invention, patents, and external publications.

• Define and lead a long term research agenda

About the team

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.

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.

About 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.

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.

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.

Basic Qualifications

• PhD or equivalent experience in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field

• 5+ years of working knowledge of deep learning

• 5+ years of hands-on experience in predictive modeling and analysis

• 5+ years of algorithm development experience

• 5+ years of coding with at least one of the following: Java, C++, or other programming language; Additionally R, MATLAB, Python or similar scripting language

Preferred Qualifications

• Hands-on experience with a broad set of ML approaches and techniques - possibly including traditional classification and clustering, time series analysis, anomaly detection, artificial neural networks, and Bayesian non-parametric methods

• 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)

• 10+ years of relevant experience in industry and/or academia

• Authored peer-reviewed academic publications

• Extensive experience applying theoretical models to production applications

• 2+ years of experience with information security, threat detection or related domain

• Experience in production level software development including mechanisms such as CI/CD, agile development, infrastructure-as-code, containerization, serverless

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 $150,400/year in our lowest geographic market up to $260,000/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.