Deepslate is hiring for work from home roles

Deepslate

4 Remote Job Openings at Deepslate

Deepslate is hiring for remote Backend Engineer (m/f/d)

Backend Engineer (m/f/d)

Deepslate · Full Time · 3 months ago
Deepslate
🌎 Germany 💵 €60000 - €80000 per year ⭐ 2-5 yrs exp 💼 Software Development
The mission is to architect, scale, and secure the core infrastructure, focusing on user management, agent systems, performance optimization, and observability. Responsibilities include building reliable, high-performance backend systems and APIs serving millions of users and developers.
Deepslate is hiring for remote Frontend Engineer (m/f/d)

Frontend Engineer (m/f/d)

Deepslate · Full Time · 3 months ago
Deepslate
🌎 Germany 💵 €50000 - €70000 per year ⭐ 2-5 yrs exp 💼 Software Development
The role involves architecting and owning the entire front-end ecosystem, including developer dashboards, billing portals, and real-time interactive voice applications, using TypeScript and React (e.g., Next.js). Responsibilities include ensuring flawless user experience, performance optimization, production ownership, and building robust internal tooling and scalable front-end architectures.
Deepslate is hiring for remote Site Reliability Engineer (m/f/d)

Site Reliability Engineer (m/f/d)

Deepslate · Full Time · 3 months ago
Deepslate
🌎 Germany 💵 €50000 - €70000 per year ⭐ 5-10 yrs exp 💼 Software Development
The Site Reliability Engineer will be responsible for ensuring the uptime, performance, and scalability of Voice AI models that handle millions of calls by building resilient, automated infrastructure. This involves bridging development and operations to ensure smooth, efficient, and highly available AI workloads.
Deepslate is hiring for remote Model Research Engineer (m/f/d)

Model Research Engineer (m/f/d)

Deepslate · Full Time · 3 months ago
Deepslate
🌎 Germany 💵 €100K - €160K per year ⭐ 5-10 yrs exp 💼 Software Development
The primary mission is to research, train, and refine the proprietary Voice AI model by tackling complex challenges like real-time emotion recognition and subtle intonations. Responsibilities include designing and training deep learning models, optimizing them for high-speed inference, writing production-ready code, and building internal MLOps pipelines.