Mach9 Robotics Inc
MLOps/Infrastructure Engineer
Mach9 Robotics Inc, San Francisco, California, United States, 94199
About Mach9
Mach9 is at the forefront of leveraging advanced machine learning and computer vision techniques to transform raw geospatial data into actionable insights to help civil engineers build and maintain infrastructure globally. Our first
product , Mach9 Digital Surveyor, helps surveyors automatically extract features from large-scale imagery and 3D datasets over 30x faster than today's manual and labor-intensive drafting workflows, accelerating the development of cost-effective and sustainable transportation and utility infrastructure. Mach9 supports leading asset owners and engineering and construction organizations globally solve the toughest engineering design, mission planning, and asset management problems. What you'll do:
Design, implement, and maintain robust, scalable pipelines to streamline model training, evaluation, and deployment processes.
Diagnose, troubleshoot, and resolve CUDA driver and GPU-related issues, optimizing resource allocation to support efficient model training and inference.
Implement tracking tools to log experiments, monitor metrics, and enable reproducibility across model iterations and architecture changes.
Develop and manage CI/CD pipelines specifically for machine learning workflows, ensuring reproducibility, reliability, and version control across environments.
Work closely with ML Engineers, Data Scientists, and DevOps to improve infrastructure, resolve technical issues, and ensure seamless deployment workflows.
What we're looking for:
3+ years of experience in MLOps, DevOps, or Infrastructure Engineering, with a strong understanding of machine learning workflows and deployment best practices.
Strong knowledge of ML deployment and runtime technologies, including CUDA.
Experience in deploying and managing machine learning models in production environments.
Ability to independently manage and track progress on projects, demonstrating a high degree of self-motivation and accountability.
#J-18808-Ljbffr
Mach9 is at the forefront of leveraging advanced machine learning and computer vision techniques to transform raw geospatial data into actionable insights to help civil engineers build and maintain infrastructure globally. Our first
product , Mach9 Digital Surveyor, helps surveyors automatically extract features from large-scale imagery and 3D datasets over 30x faster than today's manual and labor-intensive drafting workflows, accelerating the development of cost-effective and sustainable transportation and utility infrastructure. Mach9 supports leading asset owners and engineering and construction organizations globally solve the toughest engineering design, mission planning, and asset management problems. What you'll do:
Design, implement, and maintain robust, scalable pipelines to streamline model training, evaluation, and deployment processes.
Diagnose, troubleshoot, and resolve CUDA driver and GPU-related issues, optimizing resource allocation to support efficient model training and inference.
Implement tracking tools to log experiments, monitor metrics, and enable reproducibility across model iterations and architecture changes.
Develop and manage CI/CD pipelines specifically for machine learning workflows, ensuring reproducibility, reliability, and version control across environments.
Work closely with ML Engineers, Data Scientists, and DevOps to improve infrastructure, resolve technical issues, and ensure seamless deployment workflows.
What we're looking for:
3+ years of experience in MLOps, DevOps, or Infrastructure Engineering, with a strong understanding of machine learning workflows and deployment best practices.
Strong knowledge of ML deployment and runtime technologies, including CUDA.
Experience in deploying and managing machine learning models in production environments.
Ability to independently manage and track progress on projects, demonstrating a high degree of self-motivation and accountability.
#J-18808-Ljbffr