Senior Data Platform Engineer – Real-Time Weather ML Ops

Zeus AI; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Health insurance

401k retirement options

Flexible work arrangements

Co-working space benefit

Job summary

Zeus AI, a remote-first company advancing Earth observation AI, is seeking a senior software engineer to own the data infrastructure supporting near real-time satellite feeds and model outputs.

You will build and optimize data pipelines, ensure uptime, enable cloud-based serving via APIs and visualizations, and drive DevOps best practices across the stack in a fast-moving, research-driven environment. Join scientists and engineers applying ML to weather forecasting and climate solutions.

Qualifications

• 5+ years of backend and data engineering experience.
• Experience with geospatial datasets and processing.
• Experience operating live data pipelines with uptime requirements.
• Strong understanding of CI/CD, IaC, and DevOps practices for data platforms.
• Experience with cloud platforms such as AWS, Azure, and GCP.
• Ability to independently drive technical projects end to end.

Responsibilities

• Own the data platform powering ML weather models and real-time inference.
• Design, implement, and operate robust pipelines to ingest, process, and serve multi-dimensional remote sensing datasets.
• Maintain systems to monitor data integrity, pipeline health, and computational performance.
• Lead platform engineering best practices across CI/CD, infrastructure as code, testing, deployments, and operational readiness.

Skills

Backend engineering

Data engineering

DevOps

CI/CD

Cloud computing

Geospatial data

Tools

AWS

Azure

GCP

Lambda

Job description

Zeus AI, a remote-first company advancing Earth observation AI, is seeking a senior software engineer to own the data infrastructure supporting near real-time satellite feeds and model outputs.

You will build and optimize data pipelines, ensure uptime, enable cloud-based serving via APIs and visualizations, and drive DevOps best practices across the stack in a fast-moving, research-driven environment. Join scientists and engineers applying ML to weather forecasting and climate solutions.