Are you excited by the challenge of building intelligent systems that live at the edge, understand natural language, and adapt to their environment? Do you thrive at the intersection of AI, embedded systems, and real-world impact?
Join Mantra Softech as a
Senior AI Engineer
and help define the future of smart living by designing embedded AI agents
, natural language interfaces
, and predictive intelligence
for next-generation smart devices
. From LLMs to edge-deployed vision and sensor analytics, your work will power real-time decisions and intuitive user experiences - all while pushing the boundaries of machine learning innovation.
About Us - Mantra Softech
Founded in 2006,Mantra Softech
is a global leader in high-tech hardware innovation, specializing in biometric and RFID-based solutions. As we expand into the Smart Home ecosystem
, we are developing a new portfolio of IoT devices that deliver seamless, secure, and intelligent living experiences. We are building a design-led product team, and this is your opportunity to help shape the identity of a next-gen connected home.
Location :
Ahmedabad, (Full-Time | On-Site)
About The Role
We are developing the next generation of intelligent systems that combine embedded sensing, AI at the edge, predictive maintenance, and natural language interfaces. If you're excited about deploying ML pipelines in real-world hardware, turning unstructured prompts into actions or queries, and working across the spectrum of edge devices, cloud infrastructure, and AI modeling - we want to work with you.
As a Senior AI Engineer, You Will
i.
Drive research initiatives and proof-of-concepts that push the state of the art in generative AI
and large-scale machine learning
for home-automation projects.
ii.
Develop AI agents
that can interpret, plan, and act autonomously in response to multi-modal inputs
iii.
Design and implement high-throughput, low-latency AI/ML pipelines
and to operate at global scale.
iv.
Work on prompt engineering and iteratively develop LLM-based solutions
tailored to custom use cases like text-to-SQL, text-to-command, and context-aware queries
.
v. Develop and optimize AI models
for deployment on embedded hardware.
vi.
Prototype novel generative AI solutions, integrate advancements into production, and collaborate with research partners.
vii.
Integrate real-time streaming data (video/audio/sensor) into analytics pipelines and AI workflows.
viii.
Develop MLOps pipelines
: versioning, continuous training, deployment, and monitoring of models.
ix.
Collaborate on cloud infrastructure (AWS) for scalable backend and edge-cloud sync.
Required Skills
i.
Solid foundation and expertise in developing and deploying statistical ML models
ii.
Experience with ML frameworks like Scikit-learn, PyTorch, TensorFlow,OpenCV etc.
iii.
Hands-on experience with real-life signal/data processing (audio, sensor data etc.) is a must
iv.
Understanding of MLOps tools and lifecycle (e.g., MLflow, DVC, monitoring tools)
v.
Strong proficiency in Python and/or C/C++
vi.
Experience in building multi-modal AI systems (combining text, audio, sensor, vision inputs)
vii.
Familiarity with voice activity detection (VAD), wake-word detection, and speech-to-command pipelines
viii.
Hands-on experience with time-series analysis and forecasting models for predictive maintenance
ix.
Experience with GenAI, prompt engineering and LLMs along with APIs
x.
Experience with containerization (Docker) and deploying models via microservices architecture
xi.
Exposure to model quantization and embedded deployment.
xii.
Strong understanding of data annotation, synthetic data generation, and active learning workflows. Knowledge of code version management like Bit-bucket.
xiii.
Strong grasp of SQL : writing optimized queries, working with relational schemas, and integrating SQL into ML pipelines
xiv.
Exposure to NoSQL databases (e.g., MongoDB, Redis) for high-speed or unstructured data applications
xv.
Knowledge of AI safety, model robustness, and explainability techniques for production-grade systems
Preferred Skills
i.
Experience with LangChain, LlamaIndex, or custom AI agent frameworks
ii.
Knowledge of digital twins, condition monitoring, or industrial telemetry
iii.
Exposure to event-driven edge/cloud orchestration
Qualifications :
Master's degree in relevant or related field of AI/ML from Tier-I/II institute with at least 3-4 years of experience
(ref:hirist.tech)
