The Role
Design and own end-to-end pipelines for real-world time-series sensor data (eye-tracking, physiological). Develop, evaluate, and deploy ML and statistical models on-device, improve robustness across conditions, build signal-processing and sensor-fusion solutions, and collaborate with hardware, firmware, software, and research partners to translate experiments into product-ready algorithms.
Summary Generated by Built In
Find the signal. Build the algorithm. Make it work in real-time.
We build award-winning smart glasses in Vienna: hardware, firmware, software, all under one roof. The data our devices generate is rich, complex, and full of untapped potential. We're looking for someone who can take that raw time-series data, design algorithms that make sense of it, and see them through from experiment to deployment all on a product that people actually wear.
Tasks
What You'll Be Doing
* Design and own the full pipeline, from data collection and preprocessing to model conception and training, quantitative evaluation, and deployment
* Develop and iterate on algorithms for real-world time-series sensor data, including eye-tracking and physiological signals
* Build robust data collection strategies that feed high-quality training sets
* Experiment rigorously: select the right algorithms, validate results, and know when a solution is good enough to ship
* Collaborate closely with hardware, firmware, and software engineers to deploy algorithms that run with accuracy, speed, and robustness on device
* Continuously improve algorithm performance across varying real-world conditions
* Develop computational models of attention, perception, and cognitive workload
* Measure and model eye-tracking signals (gaze, pupil size, eye movements) and interpret them in the context of cognitive and neural processes
* Build advanced signal processing pipelines for noise reduction, filtering, and feature extraction
* Apply statistical modelling and machine learning to infer mental states from noisy, real-world data
* Identify gaps between theoretical constructs and observable signals, and refine models accordingly
* Critically evaluate measurement approaches to ensure cognitive metrics are meaningful, reliable, and interpretable
* Collaborate with engineers, product, software, and hardware teams to translate ideas and insights into practical algorithms and product features
* Support and design experiments, including collaborations with universities and research institutions
Requirements
What You Bring to the Team
* Strong background in machine learning, data science, statistics, applied mathematics, physics, or a related field
* Proven experience designing and training ML models, not just running existing frameworks
* Solid understanding of data acquisition, feature engineering, and model evaluation
* Proven experience in statistical analysis of time-series data
* Experience building data processing pipelines for time-series or sequential data
* Proven experience in sensor fusion and multi-modal data analysis
* Programming proficiency in Python, C++, or similar, you are comfortable owning your code end to end
* Experience working with noisy, real-world data
* Fluent English; German is welcome
Nice to have
* Experience with edge deployment or on-device inference
* PhD or strong background in computational neuroscience, cognitive science, or psychology is a strong plus, measurement quality needs to be defended, not assumed
* Familiarity with eye-tracking, physiological, or similar time-series data
* Experience with embedded or real-time systems
* Knowledge of multimodal sensor fusion
* Familiarity with neural data (EEG, fNIRS, GSR)
* Track record of publications or applied research
Benefits
What's extra?
* Salary: €3.954 – €5.500 gross/month depending on experience
* Yearly public transport card (Vienna)
* Workation within the EEA
* Dog-friendly offices
* "Inspire Days" – time to learn and recharge
* A front-row seat to how a deep-tech hardware product gets built, from PCB to shipped device
* Small, international team where your impact is visible every day
Ready to turn raw data into real understanding, and real understanding into better products?
We can't wait to meet you.
Making Future Reality – let's train it together.
Send us your application and let's take off together!
We build award-winning smart glasses in Vienna: hardware, firmware, software, all under one roof. The data our devices generate is rich, complex, and full of untapped potential. We're looking for someone who can take that raw time-series data, design algorithms that make sense of it, and see them through from experiment to deployment all on a product that people actually wear.
Tasks
What You'll Be Doing
* Design and own the full pipeline, from data collection and preprocessing to model conception and training, quantitative evaluation, and deployment
* Develop and iterate on algorithms for real-world time-series sensor data, including eye-tracking and physiological signals
* Build robust data collection strategies that feed high-quality training sets
* Experiment rigorously: select the right algorithms, validate results, and know when a solution is good enough to ship
* Collaborate closely with hardware, firmware, and software engineers to deploy algorithms that run with accuracy, speed, and robustness on device
* Continuously improve algorithm performance across varying real-world conditions
* Develop computational models of attention, perception, and cognitive workload
* Measure and model eye-tracking signals (gaze, pupil size, eye movements) and interpret them in the context of cognitive and neural processes
* Build advanced signal processing pipelines for noise reduction, filtering, and feature extraction
* Apply statistical modelling and machine learning to infer mental states from noisy, real-world data
* Identify gaps between theoretical constructs and observable signals, and refine models accordingly
* Critically evaluate measurement approaches to ensure cognitive metrics are meaningful, reliable, and interpretable
* Collaborate with engineers, product, software, and hardware teams to translate ideas and insights into practical algorithms and product features
* Support and design experiments, including collaborations with universities and research institutions
Requirements
What You Bring to the Team
* Strong background in machine learning, data science, statistics, applied mathematics, physics, or a related field
* Proven experience designing and training ML models, not just running existing frameworks
* Solid understanding of data acquisition, feature engineering, and model evaluation
* Proven experience in statistical analysis of time-series data
* Experience building data processing pipelines for time-series or sequential data
* Proven experience in sensor fusion and multi-modal data analysis
* Programming proficiency in Python, C++, or similar, you are comfortable owning your code end to end
* Experience working with noisy, real-world data
* Fluent English; German is welcome
Nice to have
* Experience with edge deployment or on-device inference
* PhD or strong background in computational neuroscience, cognitive science, or psychology is a strong plus, measurement quality needs to be defended, not assumed
* Familiarity with eye-tracking, physiological, or similar time-series data
* Experience with embedded or real-time systems
* Knowledge of multimodal sensor fusion
* Familiarity with neural data (EEG, fNIRS, GSR)
* Track record of publications or applied research
Benefits
What's extra?
* Salary: €3.954 – €5.500 gross/month depending on experience
* Yearly public transport card (Vienna)
* Workation within the EEA
* Dog-friendly offices
* "Inspire Days" – time to learn and recharge
* A front-row seat to how a deep-tech hardware product gets built, from PCB to shipped device
* Small, international team where your impact is visible every day
Ready to turn raw data into real understanding, and real understanding into better products?
We can't wait to meet you.
Making Future Reality – let's train it together.
Send us your application and let's take off together!
Skills Required
- Strong background in machine learning, data science, statistics, applied mathematics, physics, or a related field
- Proven experience designing and training ML models (not just running existing frameworks)
- Solid understanding of data acquisition, feature engineering, and model evaluation
- Proven experience in statistical analysis of time-series data
- Experience building data processing pipelines for time-series or sequential data
- Proven experience in sensor fusion and multi-modal data analysis
- Programming proficiency in Python, C++, or similar, comfortable owning code end to end
- Experience working with noisy, real-world data
- Fluent English
- German language skills
- Experience with edge deployment or on-device inference
- PhD or strong background in computational neuroscience, cognitive science, or psychology
- Familiarity with eye-tracking, physiological, or similar time-series data
- Experience with embedded or real-time systems
- Familiarity with neural data (EEG, fNIRS, GSR)
- Track record of publications or applied research
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The Company
What We Do
MAKING FUTURE REALITY Being the inventor of Eye Hyper-Tracking® and pioneering the Digital Iris® technology, we constantly strive to create a new depth of connection between people and between people and the digital world. It is our mission to be at the forefront of developing technology that truly understands people’s perception of their reality around them and supports them in interacting with their world. Based on our expertise in vision research, we are working on redefining Mixed Reality with technology such as gaze-based MR and Eye Gestures. Already today, our smart glasses are used by customers worldwide for applications from remote maintenance and live consulting to efficient training and video documentation.
