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Sixone Labs is seeking a hands-on ML Engineer to build end-to-end ML systems that transform spectral, hyperspectral, and imaging data into actionable decisions for materials processing. You will work across the full stack—from sensor data ingestion and calibration to model deployment in real-world recycling operations.
The role requires strong ML fundamentals and collaboration with process teams. Hybrid work is required with four in-office days per week, and candidates should have a background
Sixone's technology uses machine learning (ML) algorithms to advance our knowledge of consumer plastics. Our goal is to pioneer an ML technology to enable the recycling of complex plastic materials. Sixone has developed technologies for process digitalization and advanced analytics, built to enable efficient plastics recycling. The bridging of our chemical database and sensor readings has been shown to work for blended plastics and plastic-based products. We believe that the economics of recycled materials can be achieved through innovative processing and materials technologies.
Overview of Role
This role focuses on building end-to-end ML systems that transform spectral, hyperspectral, and imaging data into actionable decisions for materials processing. You will work across the full stack: sensor data ingestion and calibration, feature extraction from high-dimensional spectral data, model development and model deployment into real-world recycling operations. This is a hands-on role that requires strong ML fundamentals.
This is a hybrid role that requires a consistent in-office presence four days per week.
Responsibilities
Candidate Requirements
Sixone offers a stimulating work environment that promotes creativity, curiosity, and innovation. Join the team and contribute to our mission to transform the recycling industry and promote a sustainable future.