We’re hiring a Backend Engineer- Machine Learning Engineer on behalf of one of our clients.
📍 Location: Amman, Jordan
📋 Type: Full-time | In-office
The ideal candidate is passionate about building ML models that work on edge devices and enjoy solving real-time audio challenges. You'll work with IoT systems, audio streams, and embedded environments to build smart, efficient solutions.
Key Responsibilities
- Build backend services for embedded audio ingestion, real-time signal processing, and AI workflows.
- Develop audio optimization tools for low-latency, clear, and efficient transmission.
- Handle automated audio tasks like voice activity detection, event triggers, and batch inference.
- Integrate with DSP or firmware for audio preprocessing and format conversion.
- Work with low-power edge environments and simulate system behavior under real-world constraints.
- Create and manage APIs for audio metadata, device registration, telemetry, and OTA updates.
- Support audio event reporting using protocols like MQTT or AMQP
- Collaborate closely with hardware, ML, and product teams to align system architecture.
- Maintain reusable tools for audio logging, normalization, and feature extraction.
Qualifications
- A Bachelor’s degree in Computer Engineering, Electrical Engineering, Embedded Systems, or a related technical field.
- 5 to 8 years of experience in backend development or embedded systems, with strong foundations in computer science.
- At least 3 years working in Agile teams, ideally in areas like AI, edge computing, or audio processing.
- Proficiency in at least one of the following backend languages: Python, Go, C++, or Rust.
- Experience working with audio AI tools or libraries, such as ONNX Runtime, TensorRT, or DSP frameworks.
- Good understanding of audio formats like PCM, WAV, and Opus, as well as streaming protocols such as RTP, WebRTC, or HTTP/2.
- Hands-on experience with Docker and container orchestration tools (e.g., Kubernetes) in edge/embedded environments.
- Experience working with time-series or binary-structured data, using databases like PostgreSQL, TimescaleDB, or even flat file systems.
- Familiarity with building backend APIs that manage audio metadata, device telemetry, or embedded commands, using protocols like REST or MQTT.
- Fluency in both English and Arabic is a must.
Nice to Have
- Background in embedded audio systems, low-level firmware, or DSP integration.
- Experience in edge AI and working with constrained environments.
- Familiarity with Kubernetes-like orchestration on embedded devices.
