Platform Architect (Geospatial ML)

Location: Mountain View, California, United States

US base salary: $307,000–$432,000 per year, plus bonus, equity, and benefits. Individual pay depends on work location and additional factors.

Company

hirify.global, builds and launches ambitious technologies aimed at solving large-scale global problems. Bellwether develops machine learning and geospatial data products for severe weather and climate-related risks, serving enterprise customers and governments.

What you will do

• Define and lead the end-to-end architecture and multi-year technical roadmap for the Bellwether platform.
• Architect ingestion, processing, storage, and analysis-ready pipelines for petabyte-scale multimodal Earth observation data.
• Design the MLOps foundation for distributed training, model serving, evaluation, drift detection, data lineage, and continual learning.
• Build infrastructure for production foundation-model and agentic systems with observability and explainability.
• Design secure, reliable, multi-tenant services, APIs, and data products for enterprise and government customers.
• Set standards for reliability, security, disaster recovery, cost efficiency, and technical decision-making while mentoring engineers and remaining hands-on with production code.

Requirements

• BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience.
• 10+ years building and operating large-scale distributed and full-stack ML systems, including 5+ years as an architect or technical lead for a platform spanning data, ML, and cloud infrastructure. 15+ years is expected for Principal-level consideration.
• Experience taking a platform from an early stage into robust production at scale and owning its evolution.
• Deep expertise in at least one major cloud, strongly preferably Google Cloud, including Kubernetes/GKE, serverless, networking, IAM, and Infrastructure as Code.
• Experience designing petabyte-scale batch and streaming systems.
• Hands-on experience designing production ML platforms and MLOps across training, serving, evaluation, and monitoring.
• Strong current coding skills in Python and at least one additional language such as Go, TypeScript, Java, or Rust.
• Experience designing for SLOs, fault isolation, disaster recovery, zero-trust security, and cost efficiency in high-throughput production environments.
• Ability to set direction across teams, influence without authority, mentor senior engineers, and explain architecture trade-offs to executives and customers in a high-risk, startup-like environment.

Nice to have

• Production experience with geospatial and Earth observation data and tools such as GDAL, rasterio, xarray, Zarr/COG, STAC, or Earth Engine.
• Experience designing platforms for LLM, foundation-model, or agentic applications.
• Experience building multi-tenant data platforms for enterprise or government customers, including SOC 2, FedRAMP, and customer security reviews.
• Experience with climate risk, catastrophe or risk modeling, or large-scale simulation workloads.
• Startup, founding-engineer, or open-source geospatial, data, or ML infrastructure experience.

Culture & Benefits

• Full-time employment with bonus, equity, and benefits.
• Work on high-risk, research-oriented projects with startup-like speed and ambition.
• Equal opportunity workplace with accommodation support for applicants with disabilities or special needs.