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

• 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