Sr. Applied Scientist, Applied AI & Data Architecture
Core
Define how enterprises customize foundation models by building the path from data curation and post-training to trusted evaluation and production deployment.
Role type
Senior Applied Scientist (AI/ML)
Builds
Reusable recipes, evaluation methods, open-source accelerators, and reference architectures for model customization.
Domain
Cloud AI, Machine Learning, Model Customization
Deliverable
production ML models
Required skills
Python, Java, C++, Machine Learning, Model Fine-tuning, Distillation, Reinforcement Learning, Evaluation Methodology, Synthetic Data Generation, Quantization, Distributed Systems
Preferred skills
R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, Agentic Use Cases, Inference Optimization
Technologies
Python, Java, C++, TensorFlow, PyTorch (implied), Spark, Hadoop, Open Source Frameworks
Responsibilities
Design reproducible evaluation methodologies for model selection and customization; Lead end-to-end customization engagements from data curation to production; Develop new techniques for agentic tasks and efficient model serving; Build reference architectures and open-source assets; Advise field teams and customers on model trade-offs; Mentor engineers and Solutions Architects in ML methodology.
Seniority
Senior, hands-on IC