Founding AI Engineer

We are working with a pre-seed stage startup that is building the Earth Search Engine — a platform that lets anyone analyze the live planet using natural language. They stream high-resolution satellite imagery, apply proprietary machine learning models to forecast environmental trends, and fire real-time alerts for critical changes on the ground — from wildfires to infrastructure shifts.

The Role

They are looking for a Founding Software Engineer who wants to work at the intersection of AI, geospatial data, and developer tools. This is a ground-floor opportunity — you'll be one of the first engineers on the team, shaping architecture decisions, building core product, and helping define what the company becomes.

We're looking for AI/ML engineers who can also build reliable production systems. What matters most: you're excited about geospatial intelligence, you move fast, and you care deeply about developer experience.

This person needs to have infra or MLOps experience

\*\*\*This role is onsite or hybrid in their downtown SF office. The salary range is up to 200k. Must be US Citizen or have a Green Card as, unfortunately, no visa sponsorship or transfer is provided\*\*\*

What You'll Do

• Design and build core API infrastructure powering satellite data ingestion, processing, and delivery at scale
• Develop and integrate ML models for environmental trend forecasting, change detection, and event classification
• Build and maintain Python and TypeScript SDKs and developer-facing tooling
• Work directly with satellite imagery pipelines — streaming, tiling, and serving high-resolution geospatial data
• Architect real-time alerting systems for critical geospatial events (wildfires, flooding, infrastructure changes)
• Contribute to product decisions from Day 1 — your opinions on roadmap, architecture, and UX will be heard
• Help hire and define engineering culture as the team grows

Who You Are

You might be a strong generalist engineer if you have:

• 3–5 years of software engineering experience building scalable backend systems or APIs
• Experience in Python and/or TypeScript in production environments
• Curiosity about AI/ML — you've shipped features using LLMs, built pipelines, or trained models on real data
• Strong instincts for system design: distributed systems, streaming data, latency optimization
• MLOps or infrastructure experience — you've managed model deployments, CI/CD for ML, or cloud infrastructure (AWS, GCP, or Azure)
• A bias toward shipping — you don't wait for perfect specs

Or you might be an AI/ML engineer if you have:

• 3–5 years of hands-on experience training, fine-tuning, or deploying ML models (computer vision, time-series, or geospatial a plus)
• Proficiency with ML frameworks (PyTorch, TensorFlow, JAX) and MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar)
• Infrastructure chops — you can own model serving infrastructure, manage cloud deployments, and optimize for cost and latency
• Ability to own backend services end-to-end, not just model development
• Experience building and maintaining large-scale data pipelines on cloud infrastructure

In either case, you:

• Are energized by working at an early startup where your work directly shapes the product
• Have an interest in climate tech, geospatial data, or earth observation (domain experience not required)
• Communicate clearly and thrive in a small, high-trust team
• Are comfortable with ambiguity and can define your own path when the problem is fuzzy