Applied Scientist Tax Engine jobs at Amazon in Canada, Vancouver

Join our team to build a Native AI Authoring Framework. In this role, you'll set the technical direction and build the foundation for LLM Authoring within our rendering architecture. You'll have the opportunity to create new paradigms for authoring with Generative AI that will transform how content is created and managed.This position requires a forward-thinking engineer who can translate complex technical challenges into innovative solutions. You'll collaborate with cross-functional teams to design and implement scalable systems that power our LLM authoring capabilities. In this role, you'll be a technical leader who guides architectural decisions and mentors other team members while working on technology that's pushing the boundaries of what's possible with GenAI.Key job responsibilities
- Set the technical direction for the LLM Authoring framework, designing solutions that balance immediate needs with long-term architectural vision- Design and develop optimal data structures and algorithms for the LLM authoring framework, considering performance tradeoffs and constraintsA day in the life

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

As an Sr. Applied Scientist, you'll work alongside domain experts, engineers, and other scientists to understand business problems, propose scientific solutions, and deploy them to production. You'll work on scientific initiatives for accelerating reconciliation, standardization, and onboarding. This includes:
- Leveraging GenAI/LLMs to build agentic solutions to accelerate accounting-related research/tasks and produce proactive insights.
- Building AI trust and safety in the financial domain.
- Establishing scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation, and serving.
- Developing training/evaluation datasets for model fine-tuning.
You will need to have a start-up like mindset, as you will be working an in a highly iterative and collaborative environment with SDEs, Product Managers, and Accounting stakeholders to propose ideas, experiment, and scale rapidly. You should have a keen eye for what a good user experience should look like, possess excellent written and verbal communication, and have a keen interest in learning about accounting and financial processes.

- 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 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.

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

- Are enrolled in a PhD
- Are 18 years of age or older
- Work 40 hours/week minimum and commit to 12 week internship maximum
- Can relocate to where the internship is based
- Experience programming or scripting language like Python, Java, C or C++

- Have publications at top-tier peer-reviewed conferences or journals
- Are enrolled in a academic program that is physically located in Canada

As an Applied Scientist, you'll work alongside domain experts, engineers, and other scientists to understand business problems, propose scientific solutions, and deploy them to production. You'll work on scientific initiatives for accelerating reconciliation, standardization, and onboarding. This includes:
- Leveraging GenAI/LLMs to build agentic solutions to accelerate accounting-related research/tasks and produce proactive insights.
- Building AI trust and safety in the financial domain.
- Establishing scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation, and serving.
- Developing training/evaluation datasets for model fine-tuning.
You will need to have a start-up like mindset, as you will be working an in a highly iterative and collaborative environment with SDEs, Product Managers, and Accounting stakeholders to propose ideas, experiment, and scale rapidly. You should have a keen eye for what a good user experience should look like, possess excellent written and verbal communication, and have a keen interest in learning about accounting and financial processes.

- 3+ years of solving business problems through machine learning, data mining and statistical algorithms 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
- 3+ years of programming in Java, C++, Python or related language experience
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- Experience applying theoretical models in an applied environment

As an Applied Scientist for Promise Optimization, you will spearhead the development and productionization of the latest machine learning models, addressing critical predictive and forecasting challenges. Your role will be pivotal in scaling, automating, and deploying these models, collaborating with a diverse scientific team that includes software engineers, economists, data engineers, and fellow applied scientists.This position is ideal for a forward-thinking scientist eager to apply the latest breakthroughs in AI and machine learning to solve complex, high-impact problems. Throughout your projects, you'll need to strike a delicate balance between analytical rigor and pragmatism, always prioritizing the delivery of tangible value in response to pressing business questions. You'll have the opportunity to shape the future of our organization through the innovative use of the latests technologies and methodologies.Responsibilities include:- Ensuring production models are robust, scalable, and effectively address both business needs and software engineering requirements.
- Leveraging big data and AWS technologies to scale, automate, and productionize core statistical models, enabling rapid deployment of refreshed models.
- Mentoring other researchers on the effective use of these cutting-edge tools.

- 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 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 in professional software development

In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams, product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization.

- 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