OverviewSenior Applied Scientist, Generative AI Innovation CenterJob ID: 3090928 | AWS EMEA SARL (France Branch)The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.Key job responsibilitiesCollaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challengesInteract with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to productionHelp customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimizationProvide customer and market feedback to product and engineering teams to help define product directionAbout the teamDiverse 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 CultureHere 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 GrowthWe’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 BalanceWe 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.Basic QualificationsPhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience5+ years of hands on experience with Python to build, train, and evaluate models5+ years of hands on experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniquesScientific publication track record at top-tier AI/ML/NLP conferences or journalsPreferred QualificationsDemonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customizationExperience with model optimization techniques (quantization, distillation, compression, inference optimization etc.)Experience with open-source frameworks for model customization like trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/ or similar toolsTrack record of leading the design, implementation and delivery of scientifically-complex solutions that span multiple teams.Experience driving scientific agenda and technical strategy in a team, including building consensus on technical approaches and mentoring other scientists to improve their technical capabilities.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.EEO statements and privacy policy: Amazon est un employeur engagé pour l’égalité des chances. Nous sommes convaincus qu’une main d'oeuvre diversifiée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. La protection de votre vie privée et la sécurité de vos données constituent une priorité absolue. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons, utilisons et traitons les données personnelles de nos candidats.
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