neural-network

In this role, you will build machine learning-based products/solutions, which provide descriptive, diagnostic, predictive, or prescriptive models based on data. Uses or develops machine learning algorithms, such as supervised and unsupervised learning, deep learning, reinforcement learning, Bayesian analysis, and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, Robotics, etc. Interacts with users to define requirements for breakthrough product/solutions. In either research environments or specific product environments, utilizes current programming methodologies to translate machine learning models and data-processing methods into software. Completes programming, testing, debugging, documentation and/or deployment of the solution/products. Engineers Big Data computing frameworks, data modeling, and other relevant software tools.

Qualifications

You must possess the below minimum qualifications to be initially considered for this position. Experience listed below would be obtained through a combination of your school-work/ classes/ research and/or relevant previous job and/or internship experiences.

Minimum Qualifications:

Masters with 6+ years of experience or PhD with 4+ years of experience in computer Science or Computer Engineering or Physics or Mathematics or Mechanical engineering or computational science or engineering or aerospace engineering or other related technical disciplines

• 4+ years experience in Deep Learning; Performance Analysis and modeling experience

• 4+ years of knowledge of categories of workloads including vision, NLP, recommendation engines and graph neural networks

Preferred qualifications:

• Performance tool building experience including cycle-accurate modeling, lightweight timing models, or analytical model.
• Hands-on experience with training DL models and domain knowledge of various inference usage scenarios such as real-time, multi-stream and peak throughput
• Deep Learning Training on large scale systems, communication primitives and data, model and pipeline parallelization strategies

Inside this Business Group

Intel Architecture, Graphics, and Software (IAGS) brings Intel's technical strategy to life. We have embraced the new reality of competing at a product and solution level—not just a transistor one. We take pride in reshaping the status quo and thinking exponentially to achieve what's never been done before. We've also built a culture of continuous learning and persistent leadership that provides opportunities to practice until perfection and filter ambitious ideas into execution.