Applied Scientist, AGI Customization Services

Amazon; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC is seeking an Applied Scientist to advance customization for Amazon Nova, enabling enterprises to tailor large language models with SFT, distillation, and RL techniques.

You will collaborate across teams to build scalable tooling on SageMaker, run experiments to balance accuracy, latency, and cost, and contribute to responsible AI datasets and evaluation frameworks.

Qualifications

• PhD or MS with substantial ML/CS experience.
• Experience with state-of-the-art deep learning model architectures.
• Proven ability to publish in top-tier venues or patents.

Responsibilities

• Develop customization techniques for model adaptation (SFT, distillation, RL).
• Collaborate to build enterprise-ready tooling on SageMaker.
• Design experiments to optimize accuracy, latency, and cost.
• Create evaluation datasets and robust AI safety tools.
• Communicate results to technical and non-technical stakeholders.

Skills

Java

C++

Python

Advanced ML/DL

Research & Publications

Cross-functional collaboration

Education

PhD in CS/ML/related field

MS/Equivalent with 4+ years experience

Tools

Unix/Linux

ML toolkits (TensorFlow, PyTorch)

Job description

Description

The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist to support adoption and enable customization of Amazon Nova. The role focuses on developing 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 an 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 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 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
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• 1+ years of building machine learning models for business application experience
• Master's degree, or PhD and 2+ years of applied research experience
• Experience with any programming language such as Python, Java, C++
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development
• PhD in computer science, machine learning, engineering, or related fields, or Master's degree
• PhD in computer science, computer engineering, or related field, or experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
• Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience in software development and experience in managing and troublshooting network
• Experience collaborating with cross-functional teams
• Experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning
• Experience with patents or publications at top-tier peer-reviewed conferences or journals

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

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.

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.

USA, MA, Cambridge - 142,800.00 - 193,200.00 USD annually

USA, WA, BELLEVUE - 142,800.00 - 193,200.00 USD annually

Company

Amazon.com Services LLC

Job ID

A10393389