Member of Business Staff
Hopper
Member of Business Staff
Hopper
Fast inference for production voice AI
Hopper serves open-weight speech and language models for voice applications. We build the infrastructure behind them, from model runtimes and GPU scheduling to streaming APIs.
You’ll build Hopper’s customer base, from first conversations to production deployments. You’ll work with engineering on customer evaluations and help shape our pricing, partnerships, and positioning.
This is a full-time, in-person role. You’ll work from our beautiful office in San Francisco’s Financial District.
Find and win customers. Identify teams building voice products, start relevant conversations, and build a pipeline of opportunities.
Own the sales process. Understand customer needs, put together proposals, negotiate terms, and close deals.
Guide technical evaluations. Work with engineering to help customers test Hopper on their workloads and move from evaluation to production.
Grow customer relationships. Stay close after deployment, understand how customers use Hopper, and find opportunities to serve more of their workloads.
Shape how we go to market. Help develop pricing, partnerships, and messaging based on what you learn from customers.
Build a repeatable process. Keep the pipeline current, track revenue and conversion, and improve how we find, win, and grow accounts.
Experience selling technical products or growing commercial relationships, with measurable results.
Ability to explain technical products and work directly with founders and engineers.
Clear writing, careful listening, and strong negotiation skills.
Comfort working with pipeline, conversion, usage, and pricing data.
Experience with inference, voice AI, developer tools, or an early-stage company.
An extensive network of founders and executives.
A strong following on X.
Annual base salary: $300,000 USD, plus equity.
Daily lunch and dinner in the office.
Unlimited office book budget.
$1,500/month housing stipend for living within walking distance of the office.
Relocation and visa sponsorship support.
Free Equinox membership.
Hopper builds fast inference for voice AI by training speech-to-text, text-to-speech, and speech-language models on a customer’s production calls and then serving and refining them with live traffic to keep voice agents low-latency and cost-efficient. It focuses on production workloads, optimizing time-to-first-token, efficient model serving, and continuous improvement using real call data rather than static benchmarks, with work cited on hybrid Mixture-of-Experts inference and diffusion-based TTS speeds. Hopper differentiates itself by prioritizing production data and real-time feedback through end-to-end inference and model-serving for voice agents, backed by YC and based in San Francisco. Its goal is to enable fast, accurate, and cost-effective voice AI in production by continually training on live data, deploying low-latency models, and iterating as calls flow through the system.
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