Graphics SW Engineer (Applied and Distributed ML) @ Intel - Santa Clara, CA
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Intel develops best in class graphics and GPGPU technology that is a critical part of our major product lines. We are looking for a problem solver Graphics SW engineer to join the GPGPU Tech Research Machine Learning team. The opportunity involves performing measurements and analysis of (distributed) machine learning workloads and developing optimizations to improve training and inference speed of (large) ML models used in production. We offer the unique opportunity to work across all layers of the hardware and software stack. Opportunities exist for applying and/or optimizing DL/ML models that improve the quality and/or performance of a rasterizing or ray-tracing based graphics pipeline.
Responsibilities will include a subset from the list below, but are not limited to:
- Implementing state-of-the-art machine learning models including those that scale across nodes.
- Profiling ML workloads on a distributed GPGPU cluster.
- Analyzing bottlenecks and performance trade-offs.
- Developing optimizations to speed up training and inference for a variety of models.
Behavioral traits that we are looking for:
- Great communication and problem solving skills
Minimum skills and experience:
- Bachelor’s degree in Computer Science, Computer/Electrical Engineering, or a related field with minimum 1+ years educational or work experience. Or Master’s in the same field.
Your experience must be in the following:
- Focus in machine learning (reinforcement learning, natural language processing, recommender systems, super resolution), distributed systems, or parallel computing.
- Programming skills: Python, PyTorch, TensorFlow, or C/C++
- GPU/Graphics and Data analysis
Preferred skills and experience:
An ideal candidate will have experience in one or more of the following:
- State-of-the-art machine learning models in image/video/graphics processing, reinforcement learning, natural language processing and/or recommender systems.
- Data parallelism, model parallelism and/or hybrid parallelism for training of large models and large data sets
- Systems-level optimization of distributed systems (e.g., data movement, network protocols, task schedulers)
Inside this Business Group
At the Bachelor's level: this position is not eligible for Intel immigration sponsorship.
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.
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All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
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