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Hardware/Software Co-Design Engineer

About the Team

Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large scale optimization, active learning, among other topics.

The Scaling team builds robust and scalable software and hardware to support our research efforts. It also offers core development services for mission critical goals and applications. 

We’re expanding our team to work more closely with our partners on hardware optimization and co-design, and are looking for engineers who cut across the stack from at scale ML model/workload understanding through system architecture to microarchitecture. This team will be responsible for working with partners to optimize their hardware for our workloads from early concept stage through production.

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.

In this role, you will:

  • 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.

You might thrive in this role if you have:

  • 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.

  • Able to actively collaborate with ML engineers, kernel writers, compiler developers, system engineers, chip architects/microarchitects

These attributes are nice to have:

  • PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing. Compilers or other Systems

  • Strong understanding of LLMs and challenges related to their training and inference 

Benefits and Perks

  • Medical, dental, and vision insurance for you and your family

  • Mental health and wellness support

  • 401(k) plan with 4% matching

  • Unlimited time off and 18+ company holidays per year

  • Paid parental leave (20 weeks) and family-planning support

  • Annual learning & development stipend ($1,500 per year)

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. 

OpenAI Affirmative Action and Equal Employment Opportunity Policy Statement

For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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What You Should Know About Hardware/Software Co-Design Engineer, OpenAI

Join OpenAI as a Hardware/Software Co-Design Engineer and help shape the future of technology! Here at OpenAI, we’re on a mission to discover the path to safe, beneficial AGI, and our Scaling team plays a crucial role in that journey. We’re expanding our efforts to optimize hardware for machine learning workloads and we're on the hunt for talented engineers who can navigate the complexities of system architecture, hardware optimization, and co-design. In this role, you'll collaborate closely with our kernel, compiler, and machine learning engineers to ensure that the hardware we develop meets their specific needs, focusing on performance and programmability. You’ll work with hardware vendors to influence and develop future architectures that optimize training and inference for our models. From performing thorough system analysis to evaluating potential partners' accelerators, your input will be vital for our next-generation hardware solutions. This position is based in sunny San Francisco and embraces a hybrid work model, giving you flexibility while still benefiting from in-person collaboration three days a week. If you thrive in challenging environments and enjoy tackling system-wide networking bottlenecks while ensuring efficient distribution of large-scale models, this is the perfect opportunity for you at OpenAI. With a competitive benefits package and a strong commitment to the professional growth of our team members, we’re dedicated to ensuring that your time with us is both rewarding and empowering. Come and contribute your expertise towards a future where AI benefits everyone!

Frequently Asked Questions (FAQs) for Hardware/Software Co-Design Engineer Role at OpenAI
What are the main responsibilities of a Hardware/Software Co-Design Engineer at OpenAI?

As a Hardware/Software Co-Design Engineer at OpenAI, you will be responsible for co-designing future hardware for programmability and performance, collaborating with hardware vendors, and working on performance estimates for critical kernels across various hardware configurations. Your role will involve building performance models, analyzing system performance, and managing communications with both internal and external partners.

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What qualifications do I need to work as a Hardware/Software Co-Design Engineer at OpenAI?

To qualify for the Hardware/Software Co-Design Engineer position at OpenAI, you should have at least 4 years of industry experience, with a focus on optimizing machine learning platforms for target hardware. A strong understanding of GPU architectures is essential, along with coding skills in C/C++ and Python. An advanced degree in a relevant field is preferred but not required.

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How does OpenAI support professional development for Hardware/Software Co-Design Engineers?

At OpenAI, we value the continuous learning of our employees. As a Hardware/Software Co-Design Engineer, you will benefit from an annual learning and development stipend of $1,500, which can be used for courses, conferences, or materials that help sharpen your skills and advance your career.

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What kind of projects will I work on as a Hardware/Software Co-Design Engineer at OpenAI?

As a Hardware/Software Co-Design Engineer, you'll work on innovative projects aimed at optimizing hardware for machine learning workloads. This includes co-design efforts with vendors, managing critical kernels, and simulating workloads to inform decisions regarding compute and memory hierarchies tailored for OpenAI’s models.

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Does OpenAI offer relocation assistance for the Hardware/Software Co-Design Engineer position?

Yes! OpenAI offers relocation assistance for new employees relocating to San Francisco to take on the Hardware/Software Co-Design Engineer role, ensuring a smooth transition into your new position and home.

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Common Interview Questions for Hardware/Software Co-Design Engineer
Can you explain your experience with software/hardware co-design?

When answering this question, focus on specific projects where you integrated software and hardware considerations. Highlight your collaborative experiences with hardware vendors and any direct impact your co-design efforts had on performance or programmability.

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What tools or techniques do you use for system performance modeling?

Discuss the specific tools you've applied for performance modeling such as benchmarks or simulation software. Emphasize your process in analyzing system components and optimizing them for machine learning efficiency.

Join Rise to see the full answer
Describe a challenging project where you improved machine learning performance on hardware.

Provide a real-world example detailing the steps you took to identify performance bottlenecks, your approach for solving them, and the results achieved. Utilizing metrics to measure performance improvements can also reinforce your success.

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What programming languages are you proficient in, and how have they helped in your role?

Detail your experiences using languages like C/C++ and Python for hardware-software interaction. Speak to specific projects where your coding skills normalized operations across platforms or enhanced computational efficiency.

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How do you collaborate with ML engineers, kernel writers, and compiler developers?

Emphasize your communication style and past experiences where collaboration led to successful outcomes. Highlight the importance of understanding each other's needs and how it contributed to optimized hardware solutions.

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What is your experience with optimizing CUDA or related programming languages?

Discuss the specific optimization techniques you’ve utilized in CUDA programming, providing examples of how these optimizations improved the acceleration of machine learning models or specific workloads.

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What influence do you believe hardware design has on ML algorithm performance?

Share your insights on the importance of hardware architecture in accelerating ML algorithms. Discuss how co-designing hardware with consideration for algorithmic needs can yield better performance and scalability.

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How would you evaluate potential hardware partners and their accelerators?

Outline your evaluation criteria such as performance benchmarks, compatibility with existing systems, and ability to meet specific workload requirements. Sensibly discuss how to make decisions based on collective hardware capabilities.

Join Rise to see the full answer
Can you describe your familiarity with deep learning computing fundamentals?

Highlight your knowledge of the core concepts of deep learning, including the types of architectures you’ve worked with. Discuss how this foundational knowledge informs your work in optimizing ML deployment on hardware.

Join Rise to see the full answer
What strategies do you employ to manage communications with external partners?

Explain your structured approach to maintaining clear communication with partners. Discuss methods for ensuring objectives and technical specifications align to achieve optimal co-design outcomes.

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OpenAI is a US based, private research laboratory that aims to develop and direct AI. It is one of the leading Artifical Intellgence organizations and has developed several large AI language models including ChatGPT.

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CULTURE VALUES
Inclusive & Diverse
Feedback Forward
Collaboration over Competition
Growth & Learning
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EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
April 19, 2025

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