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Principal DevOps / Edge AI Engineer
Principal DevOps / Edge AI EngineerMulya Technologies • Greater Bengaluru Area, India
Principal DevOps / Edge AI Engineer

Principal DevOps / Edge AI Engineer

Mulya Technologies • Greater Bengaluru Area, India
3 days ago
Job description

Principal DevOps / Edge AI Engineer

Bangalore

Founded in 2023,by Industry veterans HQ in California,US

  • We are revolutionizing sustainable AI compute through intuitive software with composable silicon

Principal DevOps / Edge AI Engineer

Overview :

You will be responsible for building, deploying, and maintaining the local infrastructure that powers high-performance multimodal AI models (text, image, audio, video) on a compact AI appliance. You’ll bridge the gap between hardware, ML inference, and user-facing applications - ensuring reliability, scalability, and efficiency of on-device AI workloads.

Key Responsibilities :

  • System Deployment & Orchestration
  • Containerize AI inference services and web applications using Docker or Podman.
  • Design lightweight orchestration layers for local systems (Kubernetes, Nomad, or custom orchestration).
  • Automate build, test, and deployment pipelines (CI / CD) for local-first AI workloads.
  • Performance Optimization & Resource Management
  • Optimize compute utilization for concurrent multimodal workloads.
  • Develop monitoring tools for system health, thermal management, and memory / bandwidth usage.
  • Tune OS, drivers, and I / O subsystems for maximum throughput and low latency.
  • Edge Infrastructure & Networking
  • Configure low-latency local networking for browser-based access to the AI appliance.
  • Set up secure local APIs and data isolation layers — ensuring zero external data leakage.
  • Integrate hardware accelerators and manage firmware updates across different SKUs.
  • Reliability, Testing, and Scaling
  • Build test harnesses to validate multimodal model performance (e.g., LLM + diffusion + ASR pipelines).
  • Implement over-the-air (OTA) update mechanisms for edge devices without exposing user data.
  • Develop monitoring dashboards and alerting for real-time performance metrics.
  • Required Qualifications :

  • Strong background in Linux systems engineering and containerization (Docker, Podman, LXC).
  • Experience deploying AI inference services locally or at the edge (llama.cpp, ollama, vLLM, ONNX).
  • Proficiency in CI / CD tools (GitHub Actions, Jenkins, ArgoCD) and infrastructure-as-code (Terraform, Ansible).
  • Expertise in GPU / accelerator optimization, CUDA stack management, or similar.
  • Solid understanding of networking, security, and firewall configurations for local appliances.
  • Scripting and automation skills (Python, Bash, Go, or Rust).
  • Preferred Qualifications :

  • Experience with embedded systems or edge AI devices (e.g., Jetson, Coral, FPGA-based accelerators).
  • experience minimum 10 years
  • Familiarity with low-bit quantization, model partitioning, or distributed inference.
  • Background in hardware / software co-design or systems integration.
  • Knowledge of browser-based local apps (WebSocket, WebRTC, RESTful APIs) and AI service backends.
  • Prior work in privacy-preserving AI systems or local-first architectures.
  • Contact : Uday

    Mulya Technologies

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