AI Model Architecture Optimization Engineer R&D
We are looking for an experienced AI Acceleration Engineer who can dive deep into large model (eg. transformer) architectures and blocks such as self/cross/multi-attention, and perform research and development of advanced techniques to accelerate these areas. The ideal candidate will have a deep understanding of large model design, AI acceleration techniques, and will integrate these advancements into the PyTorch stack. Familiarity with Python is essential, and experience with CUDA programming is highly desirable.
Key Responsibilities
• Innovate on AI model components, such as attention blocks, KV-cache strategies, layer streaming, tokenization, layer norms, and more, to improve AI model performance and scalability.
• Optimize and integrate AI acceleration techniques into the PyTorch stack, enabling efficient use across diverse hardware platforms.
• Own & drive features end to end to push the limits of large model architecture, ensuring seamless integration with existing frameworks.
• Benchmark and profile AI models to evaluate performance improvements, ensuring optimal execution on target hardware.
• Write and maintain clean, efficient code in Python, with a focus on integration with PyTorch.
• Leverage CUDA for GPU-based acceleration when necessary, optimizing the attention blocks for maximum performance.
• Work on cross-functional teams to design, implement, and test new features.
Qualifications
• Extensive experience with large AI model architectures, particularly with attention blocks and transformer models.
• Proficiency in Python and hands-on experience with the PyTorch framework.
• Strong understanding of AI acceleration techniques and their application in real-world use cases.
• Familiarity with CUDA for GPU programming is highly desirable.
• Demonstrated ability to optimize complex models for performance across different hardware environments.
• Experience in developing and deploying AI models at scale is a plus.
What You'll Gain
• Opportunity to work alongside industry experts in AI optimization, high-performance computing, and hardware acceleration.
• Hands-on experience with cutting-edge technologies at the intersection of AI and hardware acceleration.
• Exposure to open-source development and collaboration with a vibrant community.
Benefits We Offer:
At OpenInfer we offer comprehensive benefits, some include:
• Medical, Dental, and Vision benefits for you and your family
• Flexible Paid Time Off, 10 days
• Parental Leave
• 401(k) Plan with company matching
• Snacks and coffee to keep you energized
These benefits are further detailed in OpenInfer policies and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans.
How to Apply
Please send your resume and a brief cover letter to [email protected]. Include examples of your work with large AI models, attention blocks, or open-source contributions where applicable.
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Key Responsibilities
• Innovate on AI model components, such as attention blocks, KV-cache strategies, layer streaming, tokenization, layer norms, and more, to improve AI model performance and scalability.
• Optimize and integrate AI acceleration techniques into the PyTorch stack, enabling efficient use across diverse hardware platforms.
• Own & drive features end to end to push the limits of large model architecture, ensuring seamless integration with existing frameworks.
• Benchmark and profile AI models to evaluate performance improvements, ensuring optimal execution on target hardware.
• Write and maintain clean, efficient code in Python, with a focus on integration with PyTorch.
• Leverage CUDA for GPU-based acceleration when necessary, optimizing the attention blocks for maximum performance.
• Work on cross-functional teams to design, implement, and test new features.
Qualifications
• Extensive experience with large AI model architectures, particularly with attention blocks and transformer models.
• Proficiency in Python and hands-on experience with the PyTorch framework.
• Strong understanding of AI acceleration techniques and their application in real-world use cases.
• Familiarity with CUDA for GPU programming is highly desirable.
• Demonstrated ability to optimize complex models for performance across different hardware environments.
• Experience in developing and deploying AI models at scale is a plus.
What You'll Gain
• Opportunity to work alongside industry experts in AI optimization, high-performance computing, and hardware acceleration.
• Hands-on experience with cutting-edge technologies at the intersection of AI and hardware acceleration.
• Exposure to open-source development and collaboration with a vibrant community.
Benefits We Offer:
At OpenInfer we offer comprehensive benefits, some include:
• Medical, Dental, and Vision benefits for you and your family
• Flexible Paid Time Off, 10 days
• Parental Leave
• 401(k) Plan with company matching
• Snacks and coffee to keep you energized
These benefits are further detailed in OpenInfer policies and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans.
How to Apply
Please send your resume and a brief cover letter to [email protected]. Include examples of your work with large AI models, attention blocks, or open-source contributions where applicable.
Apply tot his job
Apply To this Job