Mantra Softech - Senior System Engineer - Artificial Intelligence

Description

edge-to-cloud home automation systems

embedded sensing, generative AI, predictive maintenance, and natural language interfaces

edge ML models to cloud-scale orchestration

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.