Member of Technical Staff (Inference)
About The Position
Artificial Analysis is the leading independent AI benchmarking company. We support labs, engineers and enterprises to understand AI capabilities and make critical decisions about their AI strategies. We are the go-to authority for understanding AI, from AI labs and enterprises to media, investors, and policymakers. Our benchmarks don’t just measure the cutting edge of AI, they are actively shaping the frontier. Our benchmarks and analysis are trusted by hundreds of thousands of users and are the go-to reference for leading AI labs including OpenAI, Google, Meta, NVIDIA and Anthropic, and major publications including the Wall Street Journal, Bloomberg, the Financial Times and The Economist. We are a team of 40+, on track to double by end of year, backed by Nat Friedman (GitHub, Meta), Daniel Gross (SSI, Meta), Andrew Ng (Google Brain, DeepLearning.ai, Amazon), Adam D’Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders. Language model inference is the fastest-moving market in AI: dozens of providers, constant price and performance shifts, and billions of dollars of deployment decisions riding on independent data. Our inference benchmarks are the industry’s reference point, and we’re hiring a Member of Technical Staff to drive them. You’ll own coverage of the serverless inference landscape: benchmarking endpoints across quality, speed and price, extending our methodology to new dimensions like cached pricing, endpoint accuracy and agentic performance, and working directly with the inference providers and neoclouds who ship on our numbers.
Requirements
- You should know the inference market from the inside.
- Backgrounds include: engineering, product, developer relations or technical GTM roles at inference providers and neoclouds (e.g. Together AI, Fireworks, Baseten, Cerebras, Novita, Parasail, DeepInfra, Modal, CoreWeave, Lambda, Nebius, Crusoe or similar), or teams serving models in production at scale.
- 3+ years of professional experience, including at least 2 years at, or working closely with, inference providers, neoclouds or teams serving models in production
- Strong analytical and critical thinking skills
- Proficiency in Python and data analysis
- Hands-on familiarity with the model serving stack (e.g. vLLM, SGLang, TensorRT-LLM) and inference APIs across providers
- Fluency in inference performance metrics and economics: tokens per second, time to first token, throughput versus latency trade-offs, cost per token
- Genuine, demonstrable interest and knowledge of Frontier AI. We want people who have informed opinions about where AI is heading, not just people who use AI tools
Responsibilities
- Own performance and price coverage of serverless API inference across the provider ecosystem, from frontier labs to specialist providers
- Drive new benchmarking dimensions including cached pricing, endpoint accuracy and agentic performance, keeping our measurement ahead of how the industry deploys
- Work directly with inference providers and neoclouds to benchmark their endpoints, resolve methodology questions and shape how the market measures serving performance
- Produce the analysis the industry uses to understand inference performance and economics, from throughput and time-to-first-token to price-performance frontiers
- Shape the roadmap of our inference benchmarking platform together with our engineers and pillar lead
- Embrace an AI-native workflow, using cutting-edge AI tools to generate leverage in a fast-changing industry and maintain our competitive edge in AI benchmarking
Benefits
- Competitive compensation including equity
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
