Applied Scientist II, Special Projects at Amazon SZ South 3 GmbH

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

223400.0

Posted On

22 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, AI, Collaboration, Statistical Modeling, Programming, Algorithms, Data Mining, Numerical Optimization, High-Performance Computing, Deep Learning, Natural Language Processing, Reinforcement Learning, Distributed Computing, Product Development, Research

Industry

Software Development

Description

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity. Basic Qualifications: - 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 Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development - Advance knowledge of machine learning, deep/natural learning, predictive modeling and large language models. - Experience in reinforcement learning (RL) or retrieval augmented generation (RAG) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations [https://amazon.jobs/content/en/how-we-hire/accommodations] for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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 [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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Responsibilities

You will design and implement novel AI/ML solutions for complex healthcare challenges while collaborating with cross-functional teams. Your role will involve analyzing data, generating insights, and developing statistical and ML models to drive advancements in healthcare.