Geospatial ML Engineer - Production Pipelines

Atomicmaps; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Atomic Maps is looking for a Machine Learning Engineer to lead the full ML lifecycle and enhance geospatial AI systems. This position entails building, deploying, and maintaining scalable ML models, collaborating with infrastructure and data engineering teams. Desired candidates should have strong Python skills, production ML experience, and familiarity with MLOps tools. Join a supportive startup to deepen your ML skills and tackle technical challenges in a fast-paced environment.

Qualifications

• Strong production ML experience and solid ML fundamentals.
• Experience with deploying ML models for imagery and video data.
• Strong problem-solving and communication skills.

Responsibilities

• Design and implement scalable, reproducible ML pipelines.
• Build automated feedback and retraining loops.
• Own the ML model lifecycle from training to deployment.
• Develop and deploy containerized inference services.
• Collaborate with product teams for integration and impact.

Skills

Python

Production-grade code

MLOps tools (MLflow, Kubeflow)

Machine Learning frameworks (PyTorch, TensorFlow)

Geospatial workflows

Tools

Docker

Argo Workflows

Airflow

Terraform

Job description

Atomic Maps is looking for a Machine Learning Engineer to lead the full ML lifecycle and enhance geospatial AI systems. This position entails building, deploying, and maintaining scalable ML models, collaborating with infrastructure and data engineering teams. Desired candidates should have strong Python skills, production ML experience, and familiarity with MLOps tools. Join a supportive startup to deepen your ML skills and tackle technical challenges in a fast-paced environment.