Artificial Intelligence Researcher

About Us Mantra Softech Mantra Softech is a technology leader in biometric (Face, Finger, & Iris) solutions, now building the next generation of AI-powered smart home devices. As we expand into intelligent IoT, we're forming a world-class AI team to bring real-time perception, decision-making, and automation to the edge. Join us to shape the future of connected living. Role Overview We're looking for a AI Research Engineer who thrives at the intersection of AI, embedded systems, and real-world impact. You will lead initiatives in LLMs, Edge AI, sensor fusion, ML Models and natural language interfaces to build AI-powered experiences across a new class of smart home devices. About the Role We are building the next wave of agentic AI systems that combine large language models, real-time streaming data, and edge-to-cloud intelligence. If you're passionate about GenAI applications , AI agents , and turning complex natural language prompts into production-grade actions and insights , this role will give you the opportunity to work across LLMOps, multimodal AI, and real-world deployments . This is not just a research role we're looking for someone who has hands-on experience in delivering AI systems end-to-end, from proof-of-concept to production deployment. Key Responsibilities Lead the design and development of GenAI-driven AI agents that can interpret multimodal inputs (voice, vision, text, sensors) and perform context-aware actions. Drive initiatives in agentic AI frameworks , building pipelines where LLMs interact with tools, APIs, and real-world devices. Architect and implement LLMOps workflows : continuous training, fine-tuning, versioning, monitoring, and evaluation of large models. Build and deploy real-time AI applications across cloud and edge environments with measurable performance and reliability. Deliver LLM-based interfaces for natural language to SQL, command execution, and intelligent assistants. Optimize GenAI solutions for latency, accuracy, and cost-efficiency while scaling across embedded platforms and cloud infrastructure. Collaborate with product and research teams to take prototypes into production , ensuring robust deployments and maintainability. Integrate real-time streaming data (audio/sensor) into agentic workflows and analytics pipelines. Continuously evaluate advancements in LLMs, agent frameworks (LangChain, LlamaIndex, custom orchestrators), and apply them to real-world use cases. Ensure AI system reliability through safety, robustness, and explainability techniques. Required Skills 35 years of proven experience in designing, deploying, and delivering AI/ML systems into production. Hands-on expertise in LLMs, GenAI pipelines, prompt engineering, and agentic AI . Strong track record of deploying real-world AI solutions with measurable outcomes. Proficiency in Python (and/or C/C++) , PyTorch/TensorFlow, and AI/ML frameworks. Experience in LLMOps : MLflow, DVC, monitoring, CI/CD for ML pipelines. Strong background in time-series analysis, predictive modeling , and sensor analytics. Experience with model optimization (quantization, pruning, distillation) for edge and low-latency deployment . Deep knowledge of SQL and exposure to NoSQL databases (Redis, MongoDB). Proven ability to prototype quickly and deliver production-grade AI systems on tight timelines. Preferred Skills Experience with LangChain, LlamaIndex, or custom agent orchestration frameworks . Exposure to digital twins, telemetry, and real-time condition monitoring . Knowledge of AI safety, robustness, and explainability for LLM-based systems. Hands-on experience with cloud deployment (AWS/Azure/GCP) and edge-cloud orchestration . Familiarity with microservices, Docker, Kubernetes , and scalable backend architecture. Qualifications Master's degree in AI/ML, Computer Science, or a related field from a reputed institute. 46 years of industry experience with hands-on GenAI and production deployments . Experience in Pattern Recognition and Neural Networks Strong background in Computer Science Proficiency in Natural Language Processing (NLP) Software Development skills Excellent problem-solving and analytical skills Bachelor's or Master's degree in Computer Science, AI, or related field Excellent collaboration and communication skills .