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

agentic AI systems

hands-on experience in delivering AI systems

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