{"id":2791869,"url":"https://alion.io/job/amazon-senior-applied-scientist-sagemaker-ai","title":"Senior Applied Scientist, SageMaker AI","company":{"id":19,"name":"Amazon","domain":"amazon.com","url":"https://alion.io/company/amazon","size_band":"1-10","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":78,"open_postings":4454,"ghost_share":0,"stale_share":0.888,"repost_share":0.001,"time_to_fill_p50_days":24,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States","New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":167100,"max":226100,"currency":"USD","period":"year","gross":null,"usd_annual":226100},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"C++","optional":false},{"name":"Java","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Hadoop","optional":true},{"name":"NumPy","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SciPy","optional":true},{"name":"Spark","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-09-24T00:00:00Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-11-01T14:15:27Z","board_verified":true,"closed_at":null,"days_open":38,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":38},"description":"Come join the AWS SageMaker science team in building the next generation tools to enable custom AI/ML solutions for customers.\nAWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.\nWe are looking for world class researchers with experience in one or more of the following areas: distillation, synthetic data generation (text, multimodal), agentic AI, agentic evaluations, MTRL, ML gyms.\nBasic qualifications\n- 3+ years of building machine learning models for business application experience\n- PhD, or Master's degree and 6+ years of applied research experience\n- Experience programming in Java, C++, Python or related language\n- Experience with neural deep learning methods and machine learning\nPreferred qualifications\n- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.\n- Experience with large scale distributed systems such as Hadoop, Spark etc.\nAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.\nOur 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.\nThe base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. 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