Senior Applied Scientist, AGI Customization

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)
• 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.

Pay

Base salary range: $167,100.00 - $226,100.00 USD annually

Schedule

Not specified