Lyten is seeking a Machine Learning Scientist to design, implement, and optimize models for detecting, localizing, and visualizing airborne compounds in real-world environments, contributing to the company's mission of achieving gigaton-scale decarbonization impact through advanced supermaterials like Lyten 3D Graphene™.
Requirements
- Strong background in machine learning for time-series and multivariate sensor data.
- Experience with computational fluid dynamics (CFD), plume dispersion models, or environmental modeling.
- Expertise in 3D data visualization (e.g., Unity, WebGL, Three.js, ParaView, or similar frameworks).
- Strong proficiency with Python, TensorFlow/PyTorch, and data visualization libraries.
- Familiarity with distributed sensor networks, IoT data pipelines, and real-time analytics.
- Ability to integrate physics-based models with data-driven ML approaches.
- Experience with Bayesian inference, spatiotemporal statistics, or probabilistic graphical models.
Responsibilities
- Develop and deploy ML models for detecting and quantifying airborne compounds from multivariate gas sensor data.
- Design algorithms to estimate concentration gradients, source localization, and spatiotemporal plume dispersion.
- Create 3D visualization tools for mapping gas dispersion and dynamics in the environment, integrating data from a distributed grid of sensors.
- Build scalable systems for real-time sensor data ingestion, preprocessing, and fusion across large sensor arrays.
- Implement physics-informed ML methods (e.g., CFD-informed priors, Gaussian plume models, graph neural networks for spatial grids).
- Collaborate with hardware and embedded systems engineers to ensure ML pipelines are optimized for field deployment.
- Prototype and refine 3D mapping tools that enable end-users to monitor airborne compound plumes as volumetric “cloud maps.”
Other
- Doctorate degree in a relevant field (e.g., chemistry (molecular), materials science, mechanical engineering, electrical engineering, and chemical engineering, computer science) OR Master's degree in a relevant field AND 3+ years of experience in a relevant field leading or contributing to multidisciplinary projects where scope requires reliance on the technical experience of other team members
- US Citizen or Permanent Resident due to Export Control/ITAR
- Track record of publishing, prototyping, or deploying advanced sensing/ML systems.
- Strong data storytelling skills and ability to communicate complex results with intuitive visuals.
- Principals only; third party or agency submitted candidates will not be considered.
