Role overview
Note: The job is a remote job and is open to candidates in USA. Atomic Maps is a small, dynamic geospatial software and data consulting startup. They are seeking a Machine Learning Lead to design and operate their ML lifecycle at scale, blending hands-on technical work with leadership to ensure continuous improvement of models in production.
What you'll work on
Skills
• Experience taking models from research to production, with a focus on MLOps
• Comfortable deploying container-based models with Docker/Kubernetes
• Hands-on experience with MLflow, Kubeflow, or similar model management frameworks
• Familiarity with multimodal model training (imagery, video, point cloud)
• Strong Python skills with experience in ML frameworks (PyTorch, TensorFlow, etc.)
• Solid understanding of data structures, SQL, and cloud storage patterns
• Excellent problem-solving, communication, and leadership skills
• Experience with geospatial or computer vision workflows
• Familiarity with cloud platforms (AWS, GCP, or Azure) and GPU-based training environments
• Exposure to 3D data processing (e.g., point clouds, meshes, radiance fields, 3D tiles)
• Knowledge of spatial AI applications such as map-building from sensor data (HD maps, AR/VR, robotics)
Company Overview
• Atomic Maps is a company that offers enterprise analytics services by helping clients get the most out of their geospatial data. It was founded in 2021, and is headquartered in Austin, Texas, USA, with a workforce of 2-10 employees. Its website is https://atomicmaps.io/.