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!
#J-18808-Ljbffr
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!
#J-18808-Ljbffr
