We are looking for an 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 an 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 business outcome.
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 external scientific venues.
A day in the life
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally.
We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work / Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life.
We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.
We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.
Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
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.
We are open to hiring candidates to work out of one of the following locations :
Seattle, WA, USA
BASIC QUALIFICATIONS
- PhD, or Master's degree and 6+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- 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.