Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence to protect the global AWS platform from fraud ? The AWS Fraud Prevention organisation is looking for a talented Sr. Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. You will help us develop fraud prevention strategies leveraging AI technologies and add to our expansive portfolio of ML based mitigations. As a member of our team, you'll work on cutting-edge projects that directly impact millions of customers, organizations, and employees every single day. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.
You’ll be part of a team of Applied Scientists, Research Scientists, Data Scientists, Investigations Analysts, and Technical & non-Technical Program Managers and Software Engineers. As an Applied Scientist, you will work directly with these folks to monitor the flavor/ trend of exploits AWS worldwide and design appropriate solutions to respond in a collaborative environment. There are no walls, and success is determined by your ability to dive deep, and understand the subtle demands new and complex services will place upon systems and teams.
As a Sr. Applied Scientist your responsibilities will include:
- Develop and apply state-of-the-art Machine Learning methods to large amounts of data from different sources to build and productionalize fraud prevention, detection and mitigation solutions
- Actively contribute to the development of our ML Ops infrastructure
- Actively contribute to the creation and delivery of our science roadmap which includes Gen AI efforts
- Work closely with software engineering teams to deploy your innovations.
- Mentor and coach junior scientists
- Publish your work at internal and external conferences/journals
- Providing on-call product support approximately once every 3 months
On Call Responsibility. This position involves on-call responsibilities to support emergent customer impacting events. Our on-call fraud escalation support occurs approximately once every 12 weeks.
This Sr. Applied Scientist is also expected to play a key role in raising the AI/ML skillset within the organization, so a passion for teaching/mentoring is important. This involves bringing deep AI/ML expertise to collaborations with other scientists, leading lunch & learn session, conducting tech talks, setting up regular office hours, evangelizing lessons learned & industry best practices, and more. The ideal candidate is one who possesses notable pedigree in ML-related academic work, along with deep, real-world, hands-on experience in executing/shipping AI-based products in a fast-paced setting. You will be looked up to as an ML expert that our organization’s leadership can rely on for guidance on AI/ML topics.
Mentorship & Career Growth: Our team is dedicated to supporting new members. We have a broad mix of experience levels, functions and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
Learn and Be Curious: We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.
Inclusion and Diversity. Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more.
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About AWS
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AWS values diverse experiences. Even if you do not meet all of the preferred 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.
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About the team
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
BASIC QUALIFICATIONS
- PhD plus experience (3+years) or MS plus experience (6+ years) in ML, NLP, computer vision, or related fields
- Experience in building machine learning models for business application
- Research expertise in deep learning
- Experience programming in Java, C++, Python or related language
- Experience in publishing research papers
- Experience in Generative Models.
PREFERRED QUALIFICATIONS
- Phd in Computer Science/Machine learning
- Experience in publications at top-tier peer-reviewed conferences or journals
- Experience working in the Fraud Prevention domain
- Excellent communication skills
- Strong skills in problem solving, programming, and computer science fundamentals
- Strong algorithm development experience
- Solid background in statistics, math, CS, machine learning and artificial intelligence
- Solid knowledge of statistics and probability
- Comfortable working in a fast paced, highly collaborative, dynamic work environment