Atomic Maps
AI

[Remote] Machine Learning Lead

Atomic Maps · Anywhere · $112k - $114k

Actively hiring Posted 8 months ago

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.

Responsibilities
• Own the design and implementation of scalable ML pipelines for training, retraining, and deploying models
• Build automated feedback loops that incorporate labeled data from imagery and other modalities
• Manage model lifecycle using MLflow, Kubeflow, or similar tools (from experiment tracking to production deployment)
• Develop and publish containerized inference engines for large-scale geospatial and computer vision workloads
• Stay current with advances in multimodal ML (imagery, video, point cloud, radiance field, 3D spatial AI) and guide Atomic’s adoption
• Collaborate with engineers and product teams to align ML capabilities with customer use cases
• Establish best practices for MLOps, reproducibility, and scalability across the organization
• Mentor and guide teammates; help shape the future growth of Atomic’s ML team

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/.

Tags & focus areas

Used for matching and alerts on DevFound
Remote Lead Machine Learning Aws Docker Kubernetes Tensorflow Pytorch Fulltime
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.