Who you are

• Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study
• 3+ years of experience developing solutions in ML systems or the ML software stack
• Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads
• Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference
• Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code
• Open-minded and collaborative team player with the willingness to help others
• Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models
• Experience working with large Vision-Language Models (VLMs)

What the job involves

• Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning
• Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system
• Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks
• Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment