Founding Data Scientist, Capacity & Pricing Optimization
Fireworks AI is hiring a Founding Data Scientist, Capacity & Pricing Optimization for a remote role open to applicants in United States. It pays $250k-$300k a year and Level rates it ; you can apply on Fireworks AI.
Level's read on this job
- On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts 52% higher than the typical data scientist posting on Level.
- This is listed as a remote role.
- The posting mentions PyTorch among its tools and skills.
- Fireworks AI has 86 other open roles on Level.
AI in this role
About Us:
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
The Role:
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.
What You'll Work On:
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.
What we’re looking for:
Minimum Qualifications
Master’s degree in Operations Research, Economics, Industrial Engineering, Statistics, or a related quantitative field with 7+ years of hands-on experience in pricing, revenue management, or optimization. PhD preferred.
Strong grounding in at least two of: stochastic optimization, revenue management and pricing, causal inference and experimental design, or combinatorial optimization.
A track record of delivering production quality models that drive direct business impact.
Strong coding skills and experience with optimization tooling & methodologies.
Ability to communicate tradeoffs and uncertainty clearly to engineers and executives.
Preferred Qualifications
Experience on capacity planning, forecasting, or pricing science teams at a cloud computing provider or marketplace business.
Familiarity with GPU infrastructure and LLM inference economics (throughput, batching, utilization, cost per token).
Experience as the first quantitative hire in a new function, building models and data pipelines from scratch.
Why Fireworks?
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
How we rate this
Founding Data Scientist, Capacity & Pricing Optimization at Fireworks AI rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $250k
- Typical data scientist job
- $165k
This posting starts 52% above the typical data scientist job. See data scientist jobs
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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