Our ideal candidates thrives in ambiguity, build collaborative relationships, moves fast, and are passionate about meaningful work. They will have the technical skills to design and build complex distributed systems that runs at AWS scale. They prefer working on small, focused teams, own their product, and love to pitch in anywhere to get the job done. They lead by example and the team naturally gravitate towards them because of their engineering expertise and decision-making ability. They can communicate effectively with a wide variety of audiences and are comfortable pitching new ideas.
We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact. You will have an opportunity to influence product and leaders.
As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products.
Prior domain knowledge in speech, natural language processing, or computer vision is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required. Candidates should possess strong software engineering skills and several years of industry experience.
Key job responsibilities
- Applying latest deep learning and natural language processing techniques to ship new features for our customer
- Convert ambiguous business questions into precise science problems
- Regularly ship deep learning models and natural language processing models that run at AWS scale
- Collaborate with engineers, clinical experts and product managers to deliver your solutions
What You'll Do:
* Collaborate with a team of Clinical experts, researchers and engineers in solving complex healthcare challenges
* Develop novel algorithms and modeling techniques for multimodal systems
* Apply latest deep learning, Gen AI and natural language processing techniques to build model-based solutions in Health domain
* Collaborate with cross-functional teams to create impactful products and services. Convert ambiguous business questions into precise science problem, and share insights/learnings from your experimentation to help product direction.
* Conduct cutting-edge research and publish in top-tier conferences and journals
What We're Looking For:
* Strong background in deep learning and multimodal systems
* Passion for applying AI to healthcare challenges
* Ability to lead and mentor research teams
* Experience in developing scalable, secure AI/ML systems
* Expertise in areas such as medical imaging, medical notes, ontologies, genomics, or clinical decision support
About the team
This team is responsible for building classical as well as GenAI solutions that directly integrate as solutions for HealthCare and Life Science users.
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.
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.
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.
Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research 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.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 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 $150,400/year in our lowest geographic market up to $260,000/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.