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
- 3–5 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.
- 4–6 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
