Software Engineer - Cloud & Model Deployment

Omnisent is pioneering scalable acoustic sensing powered by AI — transforming audio into real-time intelligence.

We build hardware + software tailored for acoustic data, designed to extract insights from complex acoustic signals. Our proprietary ultra-low-power sonic devices capture and process acoustic signals in real-time, training what we call a Large Acoustic Model (LAM) — our foundation model built to decode the rich, messy, and untapped world of non-speech audio.

We’re starting with the manufacturing industry, applying our tech to compressed air systems — one of the most overlooked sources of energy waste. From there, we’re expanding into energy, defense, space, and smart cities — sectors where sound is the next frontier.

Please note: This is an on-site position in Munich. Applicants must have a valid EU work permit and be available to work from our Munich office.

Data Ingestion & ML Inference

• Build backend services to ingest acoustic data from edge devices/gateways into the cloud
• Deploy trained ML models to run inference on real-time acoustic signals
• Develop APIs to expose model outputs (leak alerts, sensor characteristics) for use in frontend applications

System Architecture & Cloud Infrastructure:

• Design and implement cloud architecture for scalable data ingestion, real-time processing, and model deployment (Azure preferred)
• Configure storage strategies for raw sensor data and processed inference outputs
• Set up logging, monitoring, and alerting mechanisms to ensure system reliability and observability
• Implement secure user authentication and access control

Frontend Development & Data Visualization:

• Develop a real-time web dashboard showing live leak alerts, leak locations and sensor status
• Implement live update mechanisms (e.g. WebSocket or SSEs) to stream insights as data arrives
• Build visualizations for data trends, model outputs, and sensor diagnostics
• Collaborate with embedded and ML engineers to develop a digital-twin for real-time leakage classification

Basic Requirements:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or 2+ years of relevant industry experience

• 5+ years experience in backend or full-stack software development

• Strong coding skills in Python and JavaScript/TypeScript or similar languages

• 2+ years of experience with cloud platforms (preferably using Azure tools: IoT hub, Azure functions, Azure ML, Blob Storage, etc.)

• Experience deploying ML models in real-time systems and working with streaming data (e.g. using MQTT, SSE, etc)

• Familiarity with ML model packaging formats such as TorchScript, ONNX, or similar

• Experience building interactive dashboards using modern frontend frameworks (e.g., React, Svelte) and core web technologies (HTML, CSS, JavaScript)

• Valid EU work permit and physical presence in Germany (this is an on-site role in Munich)

• Fluency in English

• Preferred Qualifications:

• Master’s degree in a technical discipline (e.g., Computer Science, Software Engineering, or a related field)

• Familiarity with containerized deployment (Docker, CI/CD integration)

• Familiarity with authentication and access control mechanisms (e.g., OAuth, JWT)

• Background in monitoring or alerting systems (e.g. logging, metrics, uptime checks)

• Structured, proactive problem-solver with strong technical skills and the ability to work independently and collaboratively

• German language skills

Join us in redefining how the world listens, understands, and responds through intelligent acoustic sensing.

In your cover letter, we’d love to hear about your personal interests, what drives you, why this role feels like the right fit — and most importantly, why Omnisent.