- M.S. or Ph.D. degree in Electrical Engineering, Computer Science, Mathematics, or related technical field
- At least 5 years of industrial/academic experience in formal verification, program analysis, constraint-solving, and theorem proving
- At least 5 years of experience with SMT/SAT solvers
- At least 5 years of experience with programming languages such as Java, Scala, C/C++, Ruby, or Python and open-source technologies
Payments Security team is looking for an Applied Scientist to apply formal verification, program analysis, and constraint-solving to prove the correctness of critical systems. In this role, you will work closely with internal security teams to design and build formal verification systems that continuously assess safety and security. You will build on top of existing formal verification tools developed by AWS and develop new methods to apply those tools at scale. You will need to be innovative, entrepreneurial, and adaptable. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
- Ph.D. degree in Electrical Engineering, Computer Science, Mathematics, or related technical field
- Ability to work in a fast paced and agile development environment
- Experience developing/modifying constraint solvers
- Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements
- Excellent written and verbal technical communication with an ability to present complex technical information in a clear and concise manner to a variety of audiences
- Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead engineering efforts to meet aggressive timelines with optimal solutions
- Meets/exceeds Amazon’s leadership principles requirements for this role
- Meets/exceeds Amazon’s functional/technical depth and complexity for this role
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- A PhD in Computer Vision, NLP, Machine Learning or an equivalent highly technical field
- 1 year of modeling experience in the area of predictive modeling, NLP or computer vision
- Deep understanding of statistical modeling and deep learning techniques.
- Strong problem solving ability
- Strong written and verbal communication skills and data presentation skills.
- Proficiency in Python and SQL
- Understand business challenges by analyzing data and customer feedback
- Collaborate with tech and product teams on model building strategies and model experiment, implementation and continuous improvement
- Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems.
- Use statistics, computer vision and deep learning techniques to create scalable solutions for business problems
- Create business and analytics reports and present to the senior management teams
- Research and implement novel machine learning and statistical approaches
- 3 years of modeling experience in the area of Deep Learning, NLP or Computer Vision
- Understanding of Software Development Life Cycle (SDLC) and project planning/execution skills including estimating and scheduling.
- Ability and willingness to multi-task and learn new technologies quickly.
- Familiar with AWS machine learning technologies such as SageMaker.
- Proficiency in C/C++, Jave, and/or matlab
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.
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- Master’s in Computer Science, Mathematics, Machine Learning, or related quantitative field
- Experience programming in Java, C++, Python or related language
- Experience in Python, or another scripting language; command line usage
- Experience with various machine learning techniques and parameters that affect their performance
The Amazon Speech team designs and develops the core speech recognition technology used by numerous Amazon products including Amazon Echo, Amazon’s mobile shopping app and various other products and services.
You’ll be joining a multi-disciplinary team of software engineers and research scientists, that develop and deploy machine learning models to millions of echo devices worldwide. These models are used to wake up echo devices and are critical to magical experience our customers have come to expect.
We are looking for passionate, hard-working, and talented Applied Scientists who have experience building innovative, mission critical, high volume applications that customers love. As a Applied Scientist in our team, you will be responsible for data-driven improvements to our models. Your work will directly impact our customers in the form of products and services that make use of speech and language technology.
· Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
· Clean, analyze and select data to achieve goals
· Build and release models that elevate the customer experience and track impact over time
· Collaborate with colleagues from science, engineering and business backgrounds.
· Present proposals and results in a clear manner backed by data and coupled with actionable conclusions
· Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
- Track record of diving into data to discover hidden patterns and of conducting error/deviation analysis
- Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
- Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
- The motivation to achieve results in a fast-paced environment.
- Experience with statistical modelling / machine learning
- Strong attention to detail
- Exceptional level of organization
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Proficiency in software development
- Ability to think creatively and solve problems
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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- PhD (or equivalent Master’s Degree plus 4+ years of experience) in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
- 1+ years of hands-on experience in predictive modeling and analysis
- 1+ years of algorithm development experience
- 1+ years of coding with at least one of the following: Java, C++, or other programming language, as well as Python or similar scripting language
- 1+ years of working knowledge of Apache Spark and Scala
Amazon delights millions of customers around the world. Meet PI-Squared, the behind-the-scenes team, that enables our HR and Operations Leaders to make informed decisions and improve the overall experience of a million frontline employees and leaders throughout their journey at Amazon. Our diverse team of statisticians, machine learning experts, and social scientists strive to make Amazon HR the most scientific HR organization in the world. We form hypotheses about the best talent acquisition, talent retention, and talent development techniques, and then set out to prove or disprove them with experiments and careful data collection. We build data science products which help to drive decisions.
We are looking for a results-oriented Applied Scientist, who are a highly motivated individual and will be comfortable in a fast-paced development environment. You will help to design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment. You will collaborate with software engineering and data engineering teams to integrate successful experiments and machine learning models into large scale, highly complex production services. You will also be involved in every aspect of the production pipeline process. It will include portability, scalability, operationalization and test, manage predictive models after deployment, create reproducible pipelines, API endpoints.
You are a self-starter who can dive into a project and are as passionate about creating compelling experiences for customers as we are. Come join us to shape the future of people data at Amazon!
- Track record of peer reviewed academic publications.
- Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.
- 5+ years of relevant experience in industry and/or academia.
- Extensive experience applying theoretical models in an applied environment.
- Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods.
- Strong Experience in Structured Prediction and Dimensionality Reduction.
- Experience with defining organizational research and development practices in an industry setting
- Domain experience with threat detection techniques
- Track record of developing novel algorithms to help detect stealthy zero-day attacks