Sr. Applied Scientist, Amazon Bedrock

3 weeks ago


Santa Clara, United States Amazon.com Services LLC - A57 Full time

Amazon is seeking a passionate, talented, and inventive Senior Applied Scientist with a strong background in machine learning. Your mission will be to contribute to the development of industry-leading technology in generative AI and foundational models. As a member of our science team at Amazon AWS Bedrock, you will design and implement post-training algorithms and modeling techniques to advance the state-of-the-art. Your work will empower millions of customers to effortlessly build applications leveraging cutting-edge Multi-modal Models and LLMs. This role offers a unique opportunity to gain hands-on experience with large-scale computing resources, accelerating breakthroughs in machine learning and foundational models.Inclusive Team CultureHere 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.Work/Life BalanceOur 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 GrowthOur 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 scientist and enable them to take on more complex tasks in the future.Key job responsibilitiesBASIC QUALIFICATIONS- PhD in CS, ML or related field, or Master with equivalent years of experience- 5+ years work experience in industry environments- Experience programming in Java, C++, Python or related language- Experience developing ML models and systems to deliver product capabilities, and demonstrated ability to own problems end-to-end (able to innovate to bridge gaps and willing to learn missing knowledge)- Patents or publications at top-tier peer-reviewed conferences or journalsPREFERRED QUALIFICATIONS- Working knowledge and experience tuning large language models (multimodal) and building evaluations.- Track record of innovating and delivering outside the box novel solutions for challenging problems.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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.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.



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