Applied AI Scientist

Job Description

Intel’s Data Center and Artificial Intelligence Group (DCAI) is seeking an Applied AI Scientist to build the next-generation software/AI-defined data center and grow our AI Business. This is a technical role within the team that dives into emerging technologies with deep cloud and AI domain expertise, who is also responsible for driving product roadmap and strategy, build early pilot programs and deploy effective and targeted pilots globally.

As an Applied AI Scientist you will…

• Develop and implements new AI models to solve high-value business problems.
• Utilize familiarity with state-of-the-art AI methods and tools to perform applied research, adapting AI methods to new business problems and inventing new methods for solving them, including machine learning, deep learning, reinforcement learning, natural language processing, computer vision, timeseries prediction, tabular data modeling, or pattern finding.
• Complete the full research cycle from academic literature survey, through performing the research, developing a proof-of-concept, and providing a production-ready model.

Qualifications

Relevant experience can be obtained through schoolwork, classes, project work, internships, and/or military experience. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Education

Bachelor’s Degree in Electrical Engineering, Computer Engineering, Computer Science, Information Science, Mathematics, or related field.

Minimum Qualifications

5+ years of total experience, experience should include:

• One (or more) of the following (applied data science and distributed computing, spanning some or all of statistics, experimentation, machine learning, optimization techniques, and data engineering and architecture).
• Software development.

Preferred Qualifications

Experience in one or more of the following is considered a plus

• MS or Ph.D in a quantitative field such as Mathematics, Computer Science, Electrical Engineering or other related field(s).
• 10+ years of experience with one or more of the following Cloud and AI technologies:
• Cloud-native architectures (Containers, Kubernetes, Serverless)
• DataOps, MLOps (Kubeflow, Ray).
• Tightly-coupled and Loosely-coupled HPC frameworks.
• Deep Learning, ML Frameworks (PyTorch, TensorFlow).
• Physics-based hybrid models (Physics-informed Neural Networks, Digital Twins).
• Topological Data Analysis.
• Probabilistic Modeling (Bayesian modeling, Graphical models).
• Global optimization.
• Non-linear estimation techniques.
• Time series forecasting.
• Scaling on distributed CPU and accelerated compute.