Senior Applied Scientist, AGI Customization

Amazon Science; Sunnyvale (CA); On-site; USD 192,200 - 260,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Science’s AGI Customization Team seeks an experienced Applied Scientist in medical imaging to advance customization of foundation models, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models.

You will help design enterprise-ready tooling on SageMaker, run experiments to optimize accuracy, latency, and cost, and contribute to responsible AI datasets and model alignment for real-world applications in Sunnyvale, CA.

Qualifications

• 3+ years building ML models for business applications.
• PhD or Master’s with 6+ years of applied research.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and ML.

Responsibilities

• Contribute to the development of novel customization techniques in medical imaging, including extended post-training, continued pre-training, and advanced knowledge distillation.
• Collaborate with cross-functional teams to design enterprise-ready tooling for training techniques on SageMaker.
• Design and execute experiments to optimize model accuracy, latency, and cost across customization approaches (SFT, DPO, PPO).
• Develop and enhance training curricula for customer-specific applications.
• Create robust evaluation frameworks for model performance across domains and use cases.
• Contribute to Responsible AI toolkit and dataset creation for model alignment.
• Design and implement secure access for early model checkpoints and weights.
• Communicate technical insights to stakeholders through presentations/documentation.

Skills

ML model development

Programming (Java/C++/Python)

Deep learning

Education

PhD or MSc with 6+ years of applied research

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Hadoop

Spark

Job description

Description

The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist in the medical imaging domain foundation models. The role focuses on medical imaging domain to develop state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models.

Description

The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist in the medical imaging domain foundation models. The role focuses on medical imaging domain to develop state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models. As an Applied Scientist, you will play a important role in developing advanced customization capabilities that enable enterprises to build highly performant application-specific models without the need for training models from scratch. Your work will directly impact how companies leverage Amazon Nova models for their specific use cases.

Key job responsibilities

• Contribute to the development of novel customization techniques in medical imaging domain, including extended post-training, continued pre-training, and advanced knowledge distillation
• Collaborate with cross-functional teams to design and implement enterprise-ready tooling for various training techniques on Amazon SageMaker
• Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO)
• Develop and enhance preference learning algorithms and training curricula for customer-specific applications
• Create robust evaluation frameworks for assessing model performance across different domains and use cases
• Contribute to the development of the Responsible AI toolkit, including creating training and evaluation datasets for model alignment
• Design and implement secure access mechanisms for early model checkpoints and weights
• Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation

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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.

The 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. Learn more about our benefits at https://amazon.jobs/en/benefits.

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