AmazonApplied Scientist, AWS Security Services
Amazon is hiring an Applied Scientist, AWS Security Services in New York, United States. It pays $172k-$223k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
- The listed pay starts close to the typical applied scientist posting on Level.
- Tools and skills the posting cites include Python, Java and C.
- Level classifies it as a senior role.
- Level lists 20,000+ other open roles at Amazon.
AI in this role
Research and develop core ML and AI solutions and agentic systems for AWS security services like GuardDuty and Security Hub.
The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.
Our team also puts a high value on work-life balance. We thrive to provide a healthy balance between your personal and professional life which is crucial to your happiness and success here.
Key job responsibilities
- Invent, implement, and deploy state of the art ML/AI algorithms and systems for information security applications.
- Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.
- Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.
- Report results in a scientifically rigorous way.
- Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
Basic qualifications
- PhD in computer science, machine learning, engineering, or related fields
- 2+ years of hands-on predictive modeling and large data analysis experience
- 2+ years of programming in Java, C++, Python or related language experience
- 2+ years of building machine learning models or developing algorithms for business application experience
Preferred qualifications
- 5+ years of hands-on predictive modeling and large data analysis experience
- PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
- Extensive experience applying theoretical models in an applied environment.
- Domain experience with threat detection techniques
- Track record of developing novel algorithms to help detect stealthy zero-day attacks
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 172,400.00 - 223,400.00 USD annually
How we rate this
Applied Scientist, AWS Security Services at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- This job starts at
- $172k
- Typical applied scientist job
- $172k
This posting starts close to the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where predictive modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer vision, NLP, AI Research, Machine learning, and Predictive Modeling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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