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Job Details
Posted date: Aug 06, 2024
There have been 212 jobs posted with the title of Sr. Applied Scientist all time at Amazon.There have been 212 Sr. Applied Scientist jobs posted in the last month.
Location: Seattle, WA
Estimated salary: $205,200
Range: $150,400 - $260,000
Description
Amazon Web Services is looking for world class scientists to join the Security Innovation team in AWS Global Services Security (GSS). GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML. This is an exciting opportunity to contribute at the intersection of AI/ML, cloud, and cybersecurity. Your primary responsibility will be to envision, experiment, prototype, and mature to scale AI/ML solutions in our products to meet the needs of our customers. You will have the opportunity to work with multiple lines of business, and learn from (and contribute to) a variety of security use cases. This is a hands-on role where success is measured by producing solutions that have measurable impact. If you have experience with large scale machine learning and have a passion for security, this will be an exciting opportunity.Key job responsibilities
* Collaborate with security and business teams to identify viable ML opportunities and develop a plan from experiments to proof-of-concept to software product.
* Conduct cutting-edge research and deliver new initiatives with potential to impact multiple teams and customers in the medium to long term.
* Invent, implement, and deploy state-of-the-art machine learning algorithms and systems for information security applications.
* Lead collaboration with software engineering teams to integrate successful experiments into large-scale, highly complex production services.
* Experiment and report results in a scientifically rigorous way.
* Advance the state of the art through invention, patents, and external publications.
* Define and lead a long term research agenda
About the team
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels 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 and enable them to take on more complex tasks in the future.
Qualifications
- PhD or equivalent experience in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field- 5+ years of working knowledge of deep learning
- 5+ years of hands-on experience in predictive modeling and analysis
- 5+ years of algorithm development experience
- 5+ years of coding with at least one of the following: Java, C++, or other programming language; Additionally R, MATLAB, Python or similar scripting language
Extended Qualifications
- Hands-on experience with a broad set of ML approaches and techniques - possibly including traditional classification and clustering, time series analysis, anomaly detection, artificial neural networks, and Bayesian non-parametric methods- Hands-on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar. Prior experience training and fine-tuning Large Language Models (LLMs)
- 10+ years of relevant experience in industry and/or academia
- Authored peer-reviewed academic publications
- Extensive experience applying theoretical models to production applications
- 2+ years of experience with information security, threat detection or related domain
- Experience in production level software development including mechanisms such as CI/CD, agile development, infrastructure-as-code, containerization, serverless
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.
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