We are seeking an Applied Scientist to help define, design, build, and operate AI-powered security solutions across the full lifecycle of open source software usage. You will work alongside a team to build intelligent automation that augments manual identification, analysis, and remediation workflows, enforces security controls for agents and human experts, and provides data-driven insights to AWS leadership.
Key job responsibilities
- Architect and build AI-powered security applications and tooling - Design and implement LLM-based systems (leveraging Bedrock, SageMaker, and state of the art patterns) for intelligent code scanning, automated solution development/deployment, and remediation alternatives.
- Transform manual processes - Reimagine and deliver change from low throughput, human-dependent processes into high volume, machine speed pipelines without sacrificing key quality metrics.
- Collaborate with and influence other leaders - The open source ecosystem has many stakeholders, and change requires listening and supporting but also influencing and leading through action.
- Drive proactive security automation - Build systems that identify and remediate security issues in deliverables (code, threat models, content) without requiring explicit builder consent at every step, moving from reactive reviews to proactive prevention
- Own operational excellence - Define and maintain SLAs, monitoring, alerting, runbooks, and incident response for services you own; participate in on-call rotation to support 24/7 availability
- Lead technical design - Produce design documents, conduct trade-off analysis, and drive alignment across organizations.
- Design and conduct scientific research using machine learning and deep learning techniques to address complex, ambiguous problems, working backwards from customer needs to invent new approaches or extend existing ones.
- Build, train, and evaluate production-quality models using frameworks such as PyTorch or TensorFlow, applying rigorous experimentation, feature engineering, and hyperparameter optimization to improve accuracy and performance.
- Write clean, maintainable code with optimal data structures and algorithms, ensuring your components integrate directly into production systems and meet high standards for operational reliability and resource efficiency.
- Collaborate with engineering and product partners to translate scientific insights into scalable solutions, clearly communicating design decisions and trade-offs to ensure long-term maintainability.
- Contribute to the scientific community by authoring or co-authoring peer-reviewed publications, mentoring less experienced scientists, and participating in technical reviews across teams.
A day in the life
You might start your morning reviewing experiment results and refining a model architecture before syncing with engineering partners on an upcoming production integration. After lunch, you could dive into a research paper relevant to a challenge your team is tackling, then prototype a new approach and set up evaluation pipelines. Later, you may join a design review to share your findings or pair with a teammate to debug a tricky data pipeline issue. Throughout, you balance hands-on scientific exploration with collaborative problem-solving.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience contributing to open source projects (e.g., submitting pull requests, reviewing code, filing or triaging issues) and driving features or fixes upstream into third-party open source projects used in production systems.
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
- Experience maintaining or co-maintaining an open source repository, including issue handling, release management, and community moderation.
- Experience with open source security practices such as vulnerability disclosure, dependency auditing, or the use of AI to analyze and remediate vulnerabilities.
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, VA, Herndon - 142,800.00 - 193,200.00 USD annually