Applied Scientist, GenAI, AWS HealthAI

Job ID: 2737618 | Amazon Development Center U.S., Inc.At AWS Health AI, we leverage AI to revolutionize healthcare and if you are passionate to make a global-scale difference in Health, we have an opportunity for you. AWS Health AI is seeking an inventive and talented Applied Scientist to join forces in the area of Natural Language Processing, Genomics, Medical Imaging or Biomedical. We are on a mission to use Gen-AI and build new innovative solutions for Healthcare and Life Sciences users. You will be involved in the entire product development cycle including customer discovery, experimentation, design, and prototyping. You will collaborate with a team of ML-focused SDEs to productionalize these solutions.Our ideal candidates thrive in ambiguity, build collaborative relationships, move fast, and are passionate about meaningful work. They will have the technical skills to design and build complex distributed systems that run 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 gravitates 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.Key job responsibilities

Applying the latest deep learning and natural language processing techniques to ship new features for our customers.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 the latest deep learning, Gen AI, and natural language processing techniques to build model-based solutions in the Health domain.Collaborate with cross-functional teams to create impactful products and services. Convert ambiguous business questions into precise science problems, 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.BASIC QUALIFICATIONS

3+ years of building models for business application experience.PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.Experience in patents or publications at top-tier peer-reviewed conferences or journals.Experience programming in Java, C++, Python, or related language.Knowledge of standard speech and machine learning techniques.PREFERRED QUALIFICATIONS

Prior experience building LLMs or GenAI based solutions.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.

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