Applied Scientist II - AMZ9674020
Amazon · Mountain View, CA · Corporate Operations
About this role
Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Mountain View, CA. The posting calls out experience with Python, Java, LLMs, NLP.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Mountain View, CA
- Department
- Corporate Operations
- Posted
- Mar 18, 2026
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Job description
from Amazon careersMULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC., Offered Position: Applied Scientist II Job Location: Mountain View, California Job Number: AMZ9674020 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Work across industries including financial services, healthcare, retail, and manufacturing, developing AI solutions tailored to each sector's requirements. Work on generative AI, natural language processing, and large-scale model training and deployment. Design custom machine learning algorithms for generative AI applications and fine-tune foundation models using customer datasets with techniques like LoRA and parameter-efficient methods. Evaluate existing ML frameworks and extend them with custom components to meet specific customer requirements. Research and apply cutting-edge ML principles including novel training methodologies and reinforcement learning techniques to create innovative solutions. Develop new algorithms for model optimization, including distillation and hardware-specific optimizations.…