В OpenAI четко описанная работа над передовыми AI-моделями, широкая техническая ответственность и зарплата выше рыночного ориентира делают эту вакансию особенно привлекательной.
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Зарплата выше рынкаАктуальные технологииЧеткая зона ответственностиЛидер в сфере AI
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Inference Performance Engineer (AI): Optimizing OpenAI's frontier model inference on TPUs across model code, kernels, and hardware with an accent on latency, throughput, hardware utilization, and inference efficiency. Focus on profiling workloads, developing optimized kernels, applying quantization, building performance benchmarks, and bringing improvements into production.
Location: San Francisco, United States; hybrid
Salary: $380K–$500K base pay annually, plus equity, performance-related bonuses for eligible employees, and benefits.
Company
OpenAI is an AI research and deployment company developing and deploying general-purpose artificial intelligence with a focus on safety and human benefit.
What you will do
Optimize frontier model execution on TPUs across the complete forward pass, including model code, kernels, and hardware interactions.
Profile workloads, identify bottlenecks, and improve latency, throughput, and hardware utilization.
Develop and optimize kernels using knowledge of the surrounding model.
Explore quantization and related techniques to improve inference efficiency while preserving model quality.
Build benchmarks and tools to measure performance, validate correctness, and guide optimization.
Partner with researchers and engineers to support new model architectures and bring performance improvements into production.
Requirements
Practical experience optimizing machine learning workloads on TPUs through training, inference, or both.
Understanding of modern model architectures and how their computation maps onto accelerator hardware.
Ability to connect detailed kernel behavior to complete-model performance and work across these stack layers.
Strong software engineering skills and a systematic approach to profiling, debugging, and validating performance improvements.
Ability to own open-ended technical problems, identify priorities, make design decisions, and deliver working solutions.
Ability to collaborate with researchers and engineers, learn unfamiliar systems, and communicate technical tradeoffs.
Nice to have
Experience with quantization or attention kernels.
Culture & Benefits
Hybrid work in San Francisco with relocation support for eligible employees.
Medical, dental, and vision insurance for employees and families, with employer HSA contributions.
401(k) retirement plan with employer match, flexible or annual paid time off depending on exemption status, paid holidays, and paid leave.
Mental health and wellness support, employer-paid life and disability coverage, and annual learning and development funding.
Equal opportunity employment and reasonable accommodations for applicants with disabilities.
Hiring process
Additional benefits details are provided during the hiring process.
Background checks are administered in accordance with applicable law.
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