Applied Scientist II, Industrial Solutions

2 weeks ago


Arlington, Virginia, United States Amazon Full time

AWS Industry Products (AIP) is a dedicated engineering division within AWS, focused on developing innovative AWS offerings by leveraging Amazon's unique innovation frameworks alongside cutting-edge digital technologies to revolutionize various sectors. We collaborate closely with industry leaders and pioneers to address challenges that hinder their progress, enabling them to seize new digital business opportunities. Our mission is to harness the extensive capabilities of AWS to make the advantages of a connected ecosystem accessible to all enterprises.

We seek Applied Scientists who are enthusiastic about reshaping industries through artificial intelligence. This role presents a distinctive chance to engage with industry clients while cultivating expertise in AI and generative AI across multiple key sectors. You will be part of a collaborative team comprising scientists, product managers, and software engineers, focused on creating AI solutions in fields such as automotive, manufacturing, healthcare, sustainability/clean energy, and supply chain/operations. A significant aspect of your role will involve advancing generative AI technologies to tackle industry-specific challenges.

Utilizing your profound knowledge in machine learning, generative AI, and software engineering, you will spearhead both tactical and strategic projects aimed at delivering reusable scientific components and services that set our industry products apart and effectively address customer needs. You will embody scientific integrity, innovation, and delivery as you partner with our segment teams on AI-driven product enhancements. Additionally, you will engage in and promote research in AI and generative AI both within Amazon and in the broader community.

Extensive familiarity with both leading-edge and emerging AI methodologies and technologies is essential. Practical experience with generative AI, foundational models, and a commitment to continuous learning in this domain are expected. Previous research or industry involvement in sustainability would be advantageous.

Inclusive Team Culture

At AWS, we celebrate our diversity and are committed to fostering an inclusive environment. We have established ten employee-led affinity groups, encompassing 40,000 employees across more than 190 chapters globally. Our innovative benefits and ongoing learning opportunities, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, reflect this commitment.

Work/Life Balance

Our team prioritizes work-life balance, emphasizing the importance of establishing a flow that energizes both personal and professional spheres. We believe that achieving the right equilibrium between your work and personal life is crucial for long-term happiness and fulfillment. We offer flexible working hours and encourage you to create your own balance.

Mentorship & Career Growth

We are dedicated to supporting new team members, fostering an environment that values knowledge sharing and mentorship. Our diverse mix of experience levels and tenures allows for one-on-one mentoring and constructive code reviews. We are invested in your career development and strive to assign projects that will help each team member evolve into a more well-rounded engineer, preparing them for more complex responsibilities in the future.

Basic Qualifications

- Master's degree or PhD

- Proficiency in programming languages such as C/C++, Python, Java, or Perl

Preferred Qualifications

- PhD

- Over 2 years of experience in developing machine learning models for business applications

Amazon is committed to creating a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status. For individuals with disabilities seeking accommodations, please refer to our resources.



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