Amazon Applied Scientist Generative AI Innovation Center 

Cambodia, Phnom Penh 

836041470

Key job responsibilities
As an Applied Scientist, you will* Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges* Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization
* Provide customer and market feedback to product and engineering teams to help define product directionA day in the life
This is a customer facing role. You will be required to travel to client locations and deliver professional services as needed.
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.Mentorship & Career Growth
We’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 Balance

- PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Master’s degree plus 5 years of relevant work experience
- 5+ years of hands on experience with Python to build, train, and evaluate models.
- 2+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high- performance computing.
- Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies.
- Scientific publication track record at top-tier AI/ML/NLP conferences or journals.

- Years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques.
- Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization
- Experience with model optimization techniques (quantization, distillation, compression, inference optimization etc.)
- Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
- Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts