Senior Applied Scientist, Next Generation Developer Experience
Amazon
Description
We are looking for a Senior Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence and machine learning. You will be part of a team building Large Language Model (LLM)-based services with the focus on enhancing the developer experience in the Cloud. The team works in close collaboration with other AWS services such as AWS Cloud9, the AWS IDE Toolkit and AWS Bedrock. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you.
As a Sr. Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs.
You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and scientific and business outcomes.
Key job responsibilities
Understand the challenges that developers face when building software today, and develop generalizable solutions.
Collaborate with developers and pave the way towards bringing your solution into production systems. Lead cross team projects and ensure technical blockers are resolved
Communicate and document your research via publishing papers in internal and external scientific venues.
A day in the life
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 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.
About the team
The Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world.
If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.
About the team
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
Basic Qualifications
PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
6+ years of relevant experience in industry and/or academia.
1+ years of experience with a programming language (C++, Java, or similar) and one scripting language (Perl, Python, or similar).
1+ years supervised and unsupervised ML approaches and techniques ranging from Regression to Deep Neural Networks.
1+ years of successfully applying ML-based solutions to complex problems in business, science, or engineering.
1+ years experience with fast prototyping and working effectively with software engineering teams.
Preferred Qualifications
Publications at top-tier peer-reviewed conferences or journals.
Depth and breadth in state-of-the-art computer vision, machine learning and natural language processing technologies.
Good written and spoken communication skills.
Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-Reduce).
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy\_page) to know more about how we collect, use and transfer the personal data of our candidates.
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