Key job responsibilities
* Set the science vision: Define a multi-year science roadmap for AI-powered security products. Identify where foundation models, agentic systems, and emerging ML techniques can fundamentally change how we detect, prevent, and respond to threats protecting Amazon Business customers.
* Invent and build, end to end: Design and personally develop novel ML solutions - from agentic architectures and RAG systems to anomaly detection and behavior modeling. You won't hand off prototypes; you'll partner with engineers and PMs to ship them into production.
* Tackle scientifically ambiguous problems: Translate messy, open-ended security challenges into well-defined scientific problems. Own the critical novelty in our systems and provide system-wide design guidance.
* Experiment with rigor and speed: Design and run offline and online experiments to validate ideas quickly. Make data-driven calls on what ships, what iterates, and what gets killed.
* Push the frontier: Stay ahead of advancements in foundation models, agentic AI, and applied ML. Evaluate emerging capabilities and make strategic build-vs-buy decisions. Publish your work at top conferences when it advances the field.
* Influence across the org: Partner with security researchers, engineers, product managers, and UX designers to turn customer needs into technical strategy. Communicate complex scientific ideas clearly to both technical and executive audiences.
* Raise the bar: Mentor applied scientists and engineers, establish scientific review practices, and set the standard for how this team does science. This is a ground-floor opportunity to shape the culture.
* Innovate with urgency: Prototype rapidly, validate with customers, and iterate. Bring a builder-scientist mindset to an environment where the best idea wins.
A day in the life
You lead from the front on a startup-paced, AI-first development team. One moment you're whiteboarding a new agentic detection architecture with principal engineers, the next you're deep in a notebook training a model or analyzing experiment results. You author science vision docs, drive design reviews, and unblock your team when the problem space gets murky. You don't just track the latest in AI, you decide what's worth betting on and lead the team in making those bets real. Every day you're advancing the science and advancing the product.
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
- Experience communicating complex ideas to technical and non-technical audiences
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.
- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience with software development lifecycle
- Experience with vLLM, SGLang, TensorRT or similar platforms in production environments, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Experience with any combination of the following: application security frameworks, identity and access controls, incident response, mobile security, cloud computing and security, AI security, threat intelligence, and penetration testing
- Experience leading, mentoring and growing teams of scientists (teams of five or more scientists)
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, TX, Austin - 167,100.00 - 226,100.00 USD annually
