Mantra Softech - Senior System Engineer - Artificial Intelligence

Description We are building the next generation of intelligent edge-to-cloud home automation systems that integrate embedded sensing, generative AI, predictive maintenance, and natural language interfaces . If you're passionate about turning unstructured prompts into actions, deploying ML pipelines on real hardware, and working across the stack from edge ML models to cloud-scale orchestration this role is for you. As a Senior AI Systems Engineer, You Will Drive AI research and productization initiatives that combine LLMs, embedded AI, and automation intelligence for smart home and industrial ecosystems. Develop AI agents capable of interpreting, reasoning, and autonomously executing context-aware tasks based on multi-modal inputs (text, audio, video, sensor). Design scalable AI/ML pipelines with high-throughput and low-latency, supporting real-time inference and feedback loops. Lead prompt engineering efforts for GenAI-driven systems like text-to-SQL, text-to-command, rule automation, and context-aware conversation interfaces. Deploy and optimize models on embedded hardware platforms such as Syntiant, NVIDIA Jetson, or ARM-based devices. Integrate real-time streaming data (sensor, audio, video) into AI analytics and decision pipelines. Develop robust MLOps pipelines including model versioning, retraining, deployment, and continuous monitoring. Collaborate on AWS-based infrastructure for edge-cloud synchronization, scalable APIs, and AI model serving. Prototype and integrate cutting-edge generative AI solutions into production systems with strong emphasis on reliability and interpretability. Required Skills Strong foundation in statistical ML, signal processing, and predictive modeling. Expertise with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, and OpenCV. Proven experience working with real-world sensor and time-series data (audio, vibration, telemetry). Deep understanding of MLOps (MLflow, DVC, CI/CD, model monitoring). Excellent programming skills in Python and/or C/C++. Experience building multi-modal AI Agentic systems combining text, audio, sensor, and visual data. Familiarity with voice activity detection (VAD), wake-word detection, and speech-to-command models. Hands-on experience in predictive maintenance and time-series forecasting. Practical experience with LLMs, prompt engineering, and GenAI APIs. Exposure to Docker, microservice deployments, and containerized model serving. Knowledge of model optimization techniques quantization, pruning, and embedded inference. Experience with data annotation, synthetic data generation, and active learning pipelines. Strong grasp of SQL (query optimization, schema design, and ML integration) and NoSQL systems (MongoDB, Redis). Understanding of AI safety, robustness, and explainability for production-grade deployments. Experience with Bitbucket, Jira, or similar version control and project management tools. Preferred Skills Hands-on experience with LangChain, LlamaIndex, or custom AI agent frameworks. Understanding of digital twins, condition monitoring, or industrial telemetry systems. Experience with event-driven edge/cloud orchestration and IoT pipeline integration. (ref:hirist.tech)