AI Systems Engineer (OCI/AI Infrastructure)
About The Position
Oracle Hardware Platform Development Engineering is seeking an AI Systems Engineer to evaluate and characterize next-generation GPU and AI accelerator platforms for Oracle Cloud Infrastructure (OCI). This hands-on engineering role involves bringing up new hardware platforms, enabling AI training and inference software stacks, running representative workloads, and analyzing system performance in real operating conditions. The engineer will determine whether workloads are limited by HBM or memory bandwidth, compute, scale-up, or scale-out, while characterizing power, thermals, memory behavior, utilization, scaling, and performance efficiency. Working in the lab, the engineer will debug hardware/software integration issues, design and execute experiments, and develop data-driven insights that explain system behavior beyond benchmark results. The role includes comparative architecture analysis across GPUs and emerging AI accelerators, evaluating architectural tradeoffs, and translating performance findings into actionable recommendations about platforms for specific AI training and inference workloads. The engineer will work with internal hardware and software teams and technology partners to help shape Oracle’s next generation of high-performance AI infrastructure. The position supports training and deployment of next-generation LLMs and generative AI models.
Requirements
- Solid knowledge of AI, GPU, and/or AI/CPU platform architecture and capabilities.
- Experience with the architecture, design, and implementation of modern server platforms across multiple architectures and vendors, including x86 and ARM.
- Strong communication skills and ability to explain complex technical issues to engineering teams and executives.
- Experience with modern high-speed buses and interconnects used in compute and AI platforms, including connectivity startup, operational robustness, and performance metrics.
- Debugging experience involving complex hardware/software interactions, including issues such as vLLM compilation failures on ROCm, CUDA memory leaks, distributed runtime failures, and kernel-level inconsistencies.
- Experience profiling compilation graphs, training workloads, and runtime execution.
Nice To Haves
- 8 or more years of experience developing software infrastructure for large-scale AI systems.
- Bachelor’s degree or higher in Computer Science or a related technical field, or equivalent experience.
- Strong debugging skills and experience analyzing and triaging AI applications from the application level to the hardware level.
- Hands-on experience maintaining or building ML training stacks involving CUDA, ROCm, NCCL, XLA, or similar technologies.
- Experience benchmarking AI workloads across different architectures.
- Background working with large-scale clusters.
- Good understanding of the internals of deep learning frameworks such as PyTorch, TensorFlow, JAX, and Ray.
Responsibilities
- Bring up and characterize new GPU and AI accelerator hardware platforms for OCI.
- Enable AI training and inference software stacks and run representative workloads.
- Analyze system performance under real operating conditions, including power, thermals, memory behavior, utilization, scaling, and performance efficiency.
- Identify whether workloads are limited by HBM or memory bandwidth, compute, scale-up, or scale-out.
- Debug hardware/software integration issues and complex interactions across application, runtime, and hardware layers.
- Design and execute experiments and develop data-driven explanations of system behavior beyond benchmark results.
- Profile compilation graphs, training workloads, and runtime execution to optimize performance and eliminate bottlenecks.
- Benchmark AI workloads across different architectures and compare GPUs with emerging AI accelerators.
- Evaluate architectural tradeoffs and provide actionable recommendations on platforms suited to particular AI training and inference workloads.
- Collaborate with internal hardware and software teams and technology partners on next-generation AI infrastructure.
- Clearly communicate technical issues and performance findings across engineering disciplines and to executives.
Benefits
- Medical, dental, and vision insurance, including expert medical opinion
- Short-term disability and long-term disability
- Life insurance and AD&D
- Supplemental life insurance for employees, spouses, and children
- Health care and dependent care Flexible Spending Accounts
- Pre-tax commuter and parking benefits
- 401(k) Savings and Investment Plan with company match
- Paid time off, including flexible or accrued vacation depending on employee eligibility and position
- 11 paid holidays
- Paid sick leave
- Paid parental leave
- Adoption assistance
- Employee Stock Purchase Plan
- Financial planning and group legal benefits
- Voluntary auto, homeowner, and pet insurance
- The posting notes that the role may be eligible for bonus, equity, and compensation deferral.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
