San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $185K – $455K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

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 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

We’re seeking a Research-Hardware Codesign Engineer to operate at the boundary between model research and silicon/system architecture. You’ll help shape the numerics, architecture, and technology bets of future OpenAI silicon in collaboration with both Research and Hardware.

Your work will include debugging gaps between rooflines and reality, writing quantization kernels, derisking numerics via model evals, quantifying system architecture tradeoffs, and implementing novel numeric RTL. This is a hands-on role for people who go looking for hard problems, get to ground truth, and drive it to production. Strong prioritization and clear, honest communication are essential.

Location: San Francisco, CA (Hybrid: 3 days/week onsite)

Relocation assistance available.

In this role you will:

• Build on our roofline simulator to track evolving workloads, and deliver analyses that quantify the impact of system architecture decisions and support technology pathfinding.

• Debug gaps between performance simulation and real measurements; clearly communicate root cause, bottlenecks, and invalid assumptions.

• Write emulation kernels for low-precision numerics and lossy compression schemes, and get Research the information they need to trade efficiency with model quality.

• Prototype numerics modules by pushing RTL through synthesis; hand off novel numerics cleanly, or occasionally own an RTL module end-to-end.

• Proactively pull in new ML workloads, prototype them with rooflines and/or functional simulation, and drive initial evaluation of new opportunities or risks.

• Understand the whole picture from ML science to hardware optimization, and slice this end-to-end objective into near-term deliverables.

• Build ad-hoc collaborations across teams with very different goals and areas of expertise, and keep progress unblocked.

• Communicate design tradeoffs clearly with explicit assumptions and confidence levels; produce a trail of evidence that enables confident execution.

You Will Thrive in this Role if:

• An exceptional track record of high-quality technical output, and a bias for shipping a prototype now and iterating later in the absence of clear requirements.

• Strong Python, and C++ or Rust, with a cautious attitude toward correctness and an intuition for clean extensibility.

• Experience writing Triton, CUDA, or similar, and an understanding of the resulting mapping of tensor ops to functional units.

• Working knowledge of PyTorch or JAX; experience in large ML codebases is a plus.

• Practical understanding of floating point numerics, the ML tradeoffs of reduced precision, and the current state of the art in model quantization.

• Deep understanding of transformer models, and strong intuition for transformer rooflines and the tradeoffs of sharded training and inference in large-scale ML systems.

• Experience writing RTL (especially for floating point logic) and understanding of PPA tradeoffs is a plus.

• Strong cross-functional communication (e.g. across ML researchers and hardware engineers); ability to slice ambiguous early-incubation ideas into concrete arenas in which progress can be made.

_To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements.

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Microsoft are looking for a highly experienced Principal Software Engineer to join their Ads Engineering Platform team to design and build next-generation Ads products that drive revenue growth and create innovative advertising experiences for users and advertisers.

About the Role

We are seeking a highly experienced software engineer to join our Ads Engineering Platform team to design and build next-generation Ads products that drive revenue growth and create innovative advertising experiences for users and advertisers. You will play a key role in evolving the core capabilities of our ad-serving infrastructure—the engine that powers advertising across Bing Search, MSN, Microsoft Start, and shopping experiences in Microsoft Edge. Our serving stack operates at massive global scale, delivering millions of ad requests per second through a geo-distributed, low-latency system that integrates real-time bidding, intelligent ranking, and ML-driven decisioning pipelines. We leverage a mix of CPU and GPU-based inference to balance latency, throughput, and cost efficiency. This role combines product innovation, distributed systems architecture, and performance engineering. You will help shape both new monetization capabilities and the next generation of model serving infrastructure that powers them.

Accountabilities

• Design and build new Ads products and monetization capabilities that unlock incremental revenue and enhance advertiser and end-user experiences.
• Lead the development of large-scale, distributed online serving systems to process millions of ad requests per second with ultra-low latency and high reliability.

The Candidate we're looking for

Experience:

• 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Proficient experience designing and operating real-time online serving or ranking systems.
• Proficient understanding of distributed systems fundamentals: concurrency, multi-threading, memory management, networking, and fault tolerance.

Personal attributes:

• Demonstrated ability to diagnose performance bottlenecks and improve latency, throughput, and cost efficiency in high-traffic systems.

Benefits

• Competitive salary range of $163,000 - $296,400 per year.
• Benefits and other compensation.
• Opportunities for professional growth and development.

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