דרושים Applied Scientist Edge Ai & Ml ב-אמזון ב-Canada, Vancouver

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.

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

Key job responsibilities
* Guide and mentor a diverse team of software engineers and technical program managers
* Foster innovation in multi-tenant storage and workflow management platforms* Create frameworks for evaluating and implementing reliable AI systems
* Build collaborative relationships across teams to drive technical excellence

- 3+ years of engineering team management experience
- 7+ years of engineering experience
- 8+ years of leading the definition and development of multi tier web services experience
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience partnering with product and program management teams
- Experience working directly within engineering teams

- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1.Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs
2.Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
3.Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies
4.Acting as a trusted advisor to customers on industry trends and emerging technologies
5.Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, 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.Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- Experience developing software code in one or more programming languages (java, python, etc.)
- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 2+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- 2+ years of experience hosting and deploying GenAI/ML solutions (e.g., for training, fine tuning, and inferences)

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