Senior Performance Engineer, Inference
AI summary of the role
This Senior Performance Engineer role at Cerebras Systems is the resident expert on inference performance and competitive pricing, benchmarking Cerebras against alternative providers.
What you’ll do
- Design standardized benchmark suites for inference workloads (code generation, summarization, multi-turn conversation, agentic tool use) enabling fair, reproducible comparisons.
- Build and continuously update a competitive pricing model covering token-based, throughput-based, and enterprise contract structures across major inference providers.
- Partner with Sales to build deal-specific competitive analyses showing total cost of ownership and performance advantages for enterprise prospects.
- Monitor industry announcements, pricing changes, and new product launches; synthesize findings into actionable briefs for Sales and Product teams.
What you’ll bring
- Deep practical experience with state-of-the-art open-source inference frameworks like vLLM, SGLang, or TensorRT-LLM.
- 5+ years of experience in ML systems, ML research engineering, or high-performance computing.
- Strong understanding of LLM inference economics: tokens, throughput, latency, batch sizes, precision trade-offs, and how these translate to customer cost.
- Strong understanding of transformer model architecture internals (attention mechanisms, KV-cache management) and how each affects memory and compute profiles.
Technologies
vLLM · SGLang · TensorRT-LLM · CUDA · Triton · TensorRT · flash-attention · KV-cache · transformer architecture · GPU kernel optimization
About Cerebras Systems
Builds wafer-scale AI processors, CS-3 systems, and cloud inference services that deliver ultra-fast training and inference without conventional multi-GPU orchestration overhead.
Growth
Source and classification
Technical pre-sales · Evidence for this classification:
GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role We are hiring a Senior Performance Engineer to join our Product team. You are an expert on state-of-the-art inference performance and will serve as our resident expert on how Cerebras stacks up against alternative inference providers on both price and performance. This role sits at the intersection of performance benchmarking from first principles and competitive intelligence. The role has two core pillars: Performance Benchmarking You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency
More from the job description
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. About The Role We are hiring a Senior Performance Engineer to join our Product team. You are an expert on state-of-the-art inference performance and will serve as our resident expert on how Cerebras stacks up against alternative inference providers on both pr [... source excerpt omitted ...] rmance. This role sits at the intersection of performance benchmarking from first principles and competitive intelligence. The role has two core pillars: Performance Benchmarking You will build, run, and maintain reproducible benchmarks that measure Cerebras inference performance for real customer workloads. This includes metrics like tokens per second, time to first token, latency under concurrency, and total cost of ownership (TCO). Competitive Pricing Intelligence You will build and maintain a living model of competitor pricing across the AI inference landscape, including cloud providers, custom silicon vendors, and inference API platforms. You will work directly with our Sa [... source excerpt omitted ...] ransformer architecture decisions—attention mechanisms, model sizing, quantization, KV-cache strategies—interact with the realities of GPU memory hierarchies and compute budgets. Responsibilities Design standardized benchmark suites for inference workloads (code generation, summarization, multi-turn conversation, agentic tool use) that enable fair, reproducible comparisons. Stay current with GPU optimization communities (CUDA, Triton, TensorRT) and evaluate how new kernel fusions, flash-attention variants, and quantization techniques shift performance ceilings. Build and continuously update a competitive pricing model covering token-based pricing, throughput-based pricing, and ent
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