Graduate Intern Technical

Job Description

The mission of Intel Labs is to drive technology leadership for Intel. This includes coordinating research and development among several business groups and aligning Intel’s strategies and technologies with future industry needs.

The Emerging Systems Lab (ESL) in the Systems, Software and Architecture Research (SSA) Group in Intel Labs driving exciting research to identify innovative systems technologies and capabilities for end-to-end (edge to cloud) infrastructure.

The Cloud Systems Research (CSR) within ESL driving breakthrough intelligent infrastructure and systems research, innovating novel AI/DL, data management, media, and graphics technologies.

Our research focus includes a) scalable and distributed intelligent visual infrastructure b) Acceleration and cross-domain optimization technologies for system efficiency c) AI automation for developer productivity.

The CSR team is looking for a graduate research intern with a strong RL, Bayesian and other optimization algorithm background development of prototypes and proofs of concept for novel applications and influence future HW/SW architectures for Intel’s data centric product and technology roadmap.

The candidate will have the opportunity to work collaboratively with a great team of researchers.

Qualifications

• Current student pursuing a BS/MS or a Ph.D. program in CS, CE, EE, CSE or related discipline.
• Research experience obtained through your educational level research and/or relevant job/internship experiences.
• Experience developing and utilizing prototyping to establish and answer a research question
• Familiarity with large-scale search space optimization methodologies, AutoML, Bayesian Optimizations
• 2 years of experience with Python, C/C++, PyTorch, MATLAB programming language
• Familiarity with computer architecture concepts

Preferred Qualifications (one or more):

• Experience with AI Frameworks (e.g. TensorFlow, Caffe, etc.) or visual data processing libraries (e.g. OpenCV)
• Experience in optimizing AI algorithm (e.g. Deep Learning, Reinforcement Learning) or mapping on accelerators.
• Experience with visual data collection, labeling and designing algorithms for visual analytics
• Experience with distributed system, database development, graph database.
• Experience with alternative representation using generative networks or hyperdimensional computing
• Familiarity with workload characterization and HW performance modeling.
• Experience with domain specific language such as Halide, MLIR, etc. The ideal candidate should exhibit behavioral traits that indicate:
• Excellent interpersonal and communications skills
• Demonstrated attention to detail and can take direction and follow-through on assignments