Principal DevOps

15 hours ago

Bengaluru, India Mulya Technologies Full time

Principal DevOps / Edge AI Engineer BangaloreFounded in 2023,by Industry veterans HQ in California,USWe are revolutionizing sustainable AI compute through intuitive software with composable siliconPrincipal DevOps / Edge AI EngineerOverview: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 & OrchestrationContainerize 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 ManagementOptimize 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 & NetworkingConfigure 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 ScalingBuild 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 yearsFamiliarity 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:UdayMulya "Mining The Knowledge Community"

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