Revenue Operations, Inference Lead

Mistral provides full-stack AI solutions, from frontier models to developer tools, applications, and compute, partnering with enterprises in finance, manufacturing, defense, healthcare, and the public sector. This role sits between the people who run the GPU fleet and the people who sell it. The role owns the commercial data, models, processes, and operating cadence behind inference capacity, pricing, and margin decisions, partnering closely with the Head of Digital Native Sales and serving as the commercial operating lead across Sales, Data Science, Inference Infrastructure, Finance, and Product. This is a build role, as little of the commercial infrastructure needed exists today.

Responsibilities

Build and own an end-to-end inference demand forecast combining pipeline, contracted commitments, and consumption trends; Combine capacity signals with pipeline demand to surface shortages, unused capacity, and supply-demand mismatches; Translate customer requirements into structured inputs for Data Science and Inference Infrastructure and help prioritize opportunities; Publish regular updates to GTM and Finance on available supply and recommended price; Partner with Finance and Pricing to build rate cards, target prices, price floors, and discount guardrails; Build and own margin sensitivity models; Build commercial telemetry for Inference (usage, consumption patterns, expansion, churn signals, leading revenue indicators); Connect capacity and usage data with pipeline, contracts, pricing, and revenue, and build self-serve reporting; Partner with Finance on long-range planning for Inference, connecting demand forecasts to capacity and capex planning; Own territory design, ICP definition, data-driven targeting, pipeline management, forecasting, and compensation plan design for the Inference and Digital Native segment; Track competitive dynamics across inference providers and adjacent players; Drive alignment across Sales, Data Science, Inference Infrastructure, Finance, and Product; Build a structured feedback loop from customer requests, adoption patterns, blocked deals, and losses into Product and Engineering

Requirements

Experience in revenue operations, business operations, strategic finance, or investment banking in a business where cost of goods is real and variable (cloud infrastructure, compute, telco, logistics, or similar); Strong SQL and comfort building own data models from raw tables to dashboard; Demonstrated ability to build unit economics and margin models that other functions trust and use; Enough technical fluency to discuss GPUs, utilization, serving efficiency, and capacity with infrastructure engineers, or clear evidence of ability to get there fast; Comfort operating with incomplete data, with a bias toward shipping rough answers quickly; Strong cross-functional leadership and ability to influence technical and commercial teams without direct authority

Nice to have

Familiarity with the inference market (provisioned throughput, per-token pricing, batch vs. real-time serving, and how major providers price); Experience with consumption- or usage-based revenue models; Experience with Salesforce, BigQuery, and BI tooling (Metabase is used); Experience sitting between a technical team and a commercial team, trusted by both sides

Benefits

Comprehensive benefits package; Healthcare coverage; Parental leave; Retirement plans; Relocation support; Wellness programs; Meal and transportation allowances; Other location-specific perks (varies by country)