Univers Global Impact AI Lab

Are you looking to build intelligent systems that move beyond digital experiments and into the physical world The Global Impact AI Lab at Univers was established to accelerate the next generation of enterprise AI and intelligent IoT innovation — transforming how industries operate, optimize resources, and build resilient infrastructure at scale.

Our mission is to translate advanced AI research into production-grade systems that enhance energy efficiency, operational performance, and sustainability across critical sectors. We focus on applied intelligence — where models and agentic systems connect directly with real-world data streams, operate in live environments, and continuously improve through operational feedback. AI is moving from promise to accountability.

Enterprises expect systems that deliver measurable outcomes in complex, high-stakes physical environments. The Global Impact AI Lab is building the intelligence layer that turns multimodal physical signals into enterprise-critical intelligence and action. If you are motivated by engineering scalable AI systems and enabling advanced models to operate reliably in real-world environments, this is an opportunity to translate innovation into measurable impact.

For more information, please visit https://univers.com/

Role Overview

As an Applied AIoT Scientist at the Global Impact AI Lab, you will design and develop AI systems that integrate heterogeneous sensing data to address real customer use cases across industrial and enterprise environments. This role sits at the intersection of advanced AI research, sensor systems, multimodal modeling, edge computing, and customer engagement. You will work closely with our GTM and engineering teams to identify high-impact AIoT opportunities, translate them into technical strategies, and drive solutions from concept to deployment.

Operating in a 0→1 environment, you will adapt and customize foundation models to reason over diverse sensor modalities, develop multimodal fusion architectures, and build agentic systems that connect perception, reasoning, and action.

You will bridge the gap between raw sensing signals and intelligent decision-making systems deployed across cloud and edge infrastructures. Beyond customer-facing innovation, you will help develop in-house AIoT capabilities that become foundational to our platform strategy, transitioning validated solutions into scalable, production-ready deployments.

This role requires deep expertise in multimodal modeling and sensor-driven systems, along with the ability to clearly articulate complex AIoT solutions to technical and executive stakeholders.

Key Responsibilities

Lead the development of AIoT solutions that integrate multimodal sensing data to address real-world industrial challenges
Operate in a 0→1 capacity — building demos and proof-of-concepts that validate technical feasibility and operational impact
Adapt and customize foundation models to process heterogeneous sensor modalities
Design and implement sensor fusion systems that combine vision, telemetry, time-series, and other signals into holistic physical-world representations
Develop agentic systems that reason over multimodal sensing data and trigger intelligent actions across connected digital and physical systems
Model physical environments for prediction, anomaly detection, optimization, and automated control decisions
Collaborate with product and engineering teams to integrate validated AIoT capabilities into scalable cloud and edge platforms
Engage directly with senior and C-level stakeholders, presenting AIoT strategies and technical roadmaps

Qualifications

Master's or Ph.D. in Computer Science, Engineering, Electrical Engineering, or related field
Strong background in deep learning, multimodal modeling, sensor fusion, and/or time series analysis
Experience working with diverse sensor modalities and IoT data environments
Familiarity with sensing architectures and data protocols in industrial or streaming systems
Experience building and deploying agentic AI systems
Experience deploying AI systems into production environments (cloud or edge) is highly valued
Ability to move quickly and iterate efficiently with customers through demos and prototypes
Excellent communication and presentation skill