The Defensive Security organization is pioneering new methods to enable innovative ways in how security teams keep Amazon safe. We are looking for a scientist to join a team of software and security engineers in building a specialized product that deals with security findings and incidents at scale.
In this role you will be a founding member of a new science initiative on a ground breaking new product. You will develop key technological A.I. advancements and ML models that will power a new suite of tools. These tools will empower 200+ security engineers world wide to keep Amazon secure.
As part of the Defensive Security organization you will enable Amazon to maintain customer trust through broad security initiatives. As the leading contributor of Defensive Security's A.I. initiatives, you will be on the forefront of resolving security findings at Amazon scale.
Key job responsibilities
- You will derive novel M.L. models for classification, and prediction using LLMs/LMMs/LAMs.
- You will design and develop scalable ML models.
- You will work with large datasets (Petabyte scale).
- You will leverage large GPU clusters to train and deploy models.
- You will work closely within software/security engineering teams to deploy your models, and test the quality of their impacts.
- You will publish your work at major conferences/journals.
- You will create written communication briefing findings, and observations for executive leadership.
- You will mentor team members in the use of your AI models.
A day in the life
A day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets and collaborate with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created.
About the team
The Defensive Security team is small, tight-knit, and co-located in Seattle and Austin. It is primarily software engineers but will be developed into a hybrid team of software engineers and security engineers. This team has tenured Amazonian leadership with a track record of mentoring, coaching, and career progression support.
About Amazon Security
Diverse Experiences — Amazon Security 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 Amazon Security? — At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
Inclusive Team Culture — In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training & 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, training, 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.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.