AWS Analytics is looking for a passionate, inventive Applied Scientist with a strong machine learning background to help create industry-leading analytics experiences, using generative AI and machine learning.
AWS provides a comprehensive set of analytics services for all data analytics needs and enables organizations of all sizes and industries to reinvent their business with data.
From storage and management, data governance, actions, and experiences, AWS offers purpose-built services that provide the best price-performance, scalability, and lowest cost.
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, 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.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
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.
Work / Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.
When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Key job responsibilities
As part of the AWS Analytics science team you will have the opportunity to apply your machine learning skills to impact some of the largest analytics services in the industry and their customers.
You will innovate by designing and building machine learning models, foundation models, and agent-based solutions instantiating them, to simplify AWS customers’ analytics journey and optimize their cost-performance profile.
You will collaborate with a talented team of applied science peers to drive scientific impact and with engineering, product, and business leaders to launch your work in production at Amazon scale.
A day in the life
- A mix of the following activities : talking to product leaders and customers to define science features; researching the state of the art and creating science plans to build them;
- building and rigorously benchmarking the science implementations of such features; partnering with engineering teams to onboard science work and launch it in production;
- preparing, publishing, and presenting scientific work at top-tier science venues and evangelizing it within the company;
- upgrading your science knowledge by participating in reading groups and science presentations by internal or external scientists;
mentoring applied science interns and science peers in all of the above functions.
About the team
We are a team dedicated to delivering transformative, science-driven analytics experiences for Amazon customers and having fun doing so.
Our leadership team fosters an inclusive team culture and encourages work-life balance to bring out the best in each team member.
Collaboration and mentorship are key tenets of our fabric. The team includes a broad mix of experience levels and tenures and is dedicated to supporting new members achieve their aspirations.
We are open to hiring candidates to work out of one of the following locations :
East Palo Alto, CA, USA Santa Clara, CA, USA
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience building machine learning models or developing algorithms for business application
- 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 in professional software development
- 3+ years of building machine learning models or developing algorithms for business application experience
- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
- Background or expertise in CS systems, particularly databases, programming languages, or compilers
- Experience in natural language processing or generative AI
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