OpenAI
Hardware / Software CoDesign Engineer - 3P
Part remote, part office, you need to live within commuting distance of a named location.
Hybrid · San Francisco
Employer listed it 6 months ago · Added 4 days ago
Been open since 6 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
$381,000–$485,000
Location
Hybrid · San Francisco
Timezone
Not stated
Contract
Full-time
Experience
Mid
Category
Software
Published by the employer
Remote flexibility
Hybrid
This role is only partly remote, the employer expects time in the office around San Francisco, Seattle, Hybrid, so you need to live within commuting distance.
What the employer says
- Source listing states candidate location: "San Francisco, Seattle, Hybrid"
- Listing mentions "Hybrid"
What Nomaders makes of it
- Not suitable if you plan to move between countries
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
About the Team
OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.
About the Role
As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity!
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Key Responsibilities
Co-design future hardware for programmability and performance with our hardware vendors
Assist hardware vendors in developing optimal kernels and add support for it in our compiler
Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory hierarchy features
Build system performance models at different abstraction levels and carry out analysis to drive decisions on scale up, scale out, front end networking
Work with machine learning engineers, kernel engineers and compiler developers to understand their vision and needs from high performance accelerators
Manage communication and coordination with internal and external partners
Influence the roadmap of hardware partners to optimize them for OpenAI’s workloads.
Evaluate potential partners’ accelerators and platforms.
As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings.
Qualifications
4+ years of industry experience, including experience harnessing compute at scale and optimizing ML platform code to run efficiently on target hardware.
Strong experience in software/hardware co-design
Deep understanding of GPU and/or other AI accelerators
Experience with CUDA, Triton or a related accelerator programming language
Experience driving Machine Learning accuracy with low precision formats
Experience with system performance modeling and analysis to optimize ML model deployment
Strong coding skills in C/C++ and Python
Are familiar with the fundamentals of deep learning computing and chip architecture/microarchitecture.
Requirements
- ·4+ years of industry experience, including experience harnessing compute at scale and optimizing ML platform code to run efficiently on target hardware.
- ·Strong experience in software/hardware co-design
- ·Deep understanding of GPU and/or other AI accelerators
- ·Experience with CUDA, Triton or a related accelerator programming language
- ·Experience driving Machine Learning accuracy with low precision formats
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, hybrid, matches where you plan to live and work.
- 2Tailor your CV to the role at OpenAI, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 5d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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$381,000–$485,000 · You'll be taken to the employer's careers page.