Cellanome, a well-funded startup, is seeking a Machine Learning Engineer to develop algorithms for data analysis and workflow automation in biology. The role involves computer vision, AI/ML, and collaboration with cross-functional teams. You will design and optimize algorithms for edge devices and GPUs.
Responsibilities
Design, develop, and optimize advanced algorithms for workflow automation, including computer vision and computational geometry components.
Develop signal-processing and image-analysis algorithms using classical methods and modern AI/ML approaches, including neural networks.
Perform system-level analysis, simulation, and validation to ensure algorithm performance meets product requirements.
Collaborate with cross-functional hardware, software, and product engineering teams to integrate algorithms into the broader software ecosystem.
Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing environments.
Create technical documentation, validation reports, and performance metrics.
Requirements
Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or related field with 5+ years of experience, or a Master's with 3+ years.
Experience developing algorithms for optimization, automation, sensing, data analysis, or image-processing applications.
