GPUs are the most expensive and supply-constrained input in AI. Our ability to effectively deploy them towards our customer demand is one of the critical inputs to our growth. We're hiring our first Data Scientist to build and own the quantitative models that drive pricing, packaging, and capacity allocation in order to optimize capacity and balance supply with demand.

The ideal candidate brings expertise at the intersection of operations research and economics with the ability to both model our market, build dynamic pricing models, and design experiments and causal studies. This is a hands-on role: you'll write production-quality code, ship models that drive real decisions, and bring an true ownership mentality to help set priorities in addition to executing on them.

Supply/Demand Modeling

Build fill-rate models for serverless inference, balancing utilization against performance and latency targets.

Model how traffic is shared and multiplexed across models and customers to set safe capacity buffers.

Pricing Optimization

Design pricing for low-utilization capacity, including spot and preemptible offerings, off-peak and overnight windows, and sub-scale capacity pools.

Develop pricing policies to optimize our capacity utilization and price-yield.

Design execute experiments and causal studies to estimate elasticity across customer segments, models, and products.

GPU Mix Optimization

Optimize the model-hardware matching across GPU generations, vendors, clouds, and regions, accounting for workload fit, substitution, and lead times.

Optimize our capacity across commitment types and terms, quantifying the tradeoff between cost, flexibility, and utilization risk to guide how we source capacity.

Founding Data Scientist, Capacity & Pricing Optimization

Responsibilities

Qualification

Required

Preferred

Company

Fireworks

More roles at Fireworks