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Gradium fournit aux développeurs et aux entreprises des API vocales en temps réel pour la transcription, la synthèse et les agents conversationnels. Sa technologie permet de créer des interactions vocales naturelles avec une faible latence.

Repères sur Gradium
Secteur
Logiciels et Internet
Modèle
B2B
Type d’entreprise
Financée par du capital-risque
Stade
Startup early-stage
Siège
Paris
Domaine officiel
gradium.ai
Création
2025 · 1 an
Financement total publié
100 M$Source ↗
Dernière levée
Seed · 2026-07-08
Montant annoncé
30 000 000 $
Offres ouvertes
6

Investisseurs mentionnés

Détails de l’offre

La description complète publiée par Gradium.

Voir l’offre originale ↗

Description de l’offre

About Gradium Gradium is a frontier voice AI company on a mission to redefine how humans interact with machines . Voice remains the most human, highest-stakes channel, but also the most broken. Long wait times, rigid IVRs, low automation, and poor handoffs create frustration on both sides of the line. Gradium is rebuilding voice from the ground up with proprietary models: real-time understanding, autonomous resolution, and seamless escalation when humans matter most.

We're a team of world-class talent, with initial traction and a clear belief: voice will be the next major frontier of applied AI. We recently raised a $100m seed round and are backed by top-tier investors. Our goal is not incremental improvement: it's to make AI-powered voice interactions feel reliable, scalable, and economically transformative. Expect early-stage reality: high autonomy, fast decisions, unreasonable ambition, few handoffs, and very little process unless it earns its place.

The Role

We're looking for a software engineer to build the core backend and infrastructure that turns Gradium's models into a product customers trust. You'll design the services behind real-time audio, keep latency low for users around the world, and make sure production stays up when it matters.

You'll work at the heart of the company, partnering closely with the founders and the research team to deploy and serve models efficiently at scale. This role exists because our edge is not just model quality but how reliably we deliver it, and that is an engineering problem that needs an owner.

What You'll Do

- Build the backend behind real-time audio: Design and build scalable backend services for real-time audio processing, and keep API latency low for users around the world.

- Make production bulletproof: Implement robust monitoring, logging, and alerting, and ensure high availability and reliability of the systems customers depend on.

- Serve models efficiently: Work with the research team to deploy and serve models in production without wasting compute.

- Own reliability at scale: Keep systems fast and dependable as traffic grows, and reason clearly about the trade-offs that come with distributed systems.

Who You Are

  • Founder mindset: You act with urgency, take full ownership, and don't wait for permission or perfect information. You are comfortable making high-stakes decisions in ambiguous environments and see the founding team as partners, not hierarchy.

- Production-obsessed engineer: You care about how systems behave under real load, not just in a demo. You measure everything, chase latency and reliability relentlessly, and take pride in things that don't break.

- Backend and distributed systems expertise: You have 5+ years of backend engineering with strong Python or Rust, hands-on experience with distributed systems, and proficiency with a major cloud platform (AWS, GCP, or Azure). You have a BS in Computer Science or equivalent practical experience.

- AI-fluent operator: You use AI-powered tools in your daily work and can always articulate why. You're relentless about pushing what's possible and reinventing how you and your team operate.

Bonus points for :

  • real-time audio or video processing systems
  • WebRTC and streaming protocols
  • Kubernetes and container orchestration
  • ML model serving infrastructure.

Still interested?

We'd love to hear about you!

Prérequis

  • Distributed systems expertise
  • Major cloud platform proficiency
  • BS in Computer Science or equivalent practical experience
  • Real-time audio or video processing systems
  • ML model serving infrastructure