Our Automation team is look for a Team Lead to help build cutting-edge systems for our mission to map and monitor the planet's forests. Verification covers everything from data ingestion, storage, indexing, transformations, modeling, training, inference, graphics, and tools. Verification consists of a Modeling and an Automation team. Each necessary to produce high-accuracy project evaluations and monitoring in a cost-effective and scalable way. As Automation Team Lead, you will build a technical roadmap across data collection, pipelines, processing, storage, indexing, access, tooling, optimizing workflows, and more to deliver high-quality forest measurements on a broad scale. You are directly responsible for technical vision and development along with leading a small, but mighty, team.
We're looking for engineers who find joy in the craft of building and want to make an impact. Engineers who push forward initiatives by asking great questions, cutting through ambiguity, and organizing to win. Engineers who are relentlessly detail-oriented, methodical in their approach to understanding trade-offs, place the highest emphasis on building, and building quickly.Position is remote but company meetings are scheduled for Pacific time zone.
- Work with leadership to set the strategy and technical roadmap of the Automation team.
- Develop robust pipelines for ingesting large volumes of sensor data, including satellite imagery, LiDAR and radar data sets.
- Be responsible for the cost-effective storage and efficient retrieval of sensor data for machine learning and scientific analysis.
- Drive the definition, development, and documentation of the APIs for Automation services.
- Work with cross-functional partners to coordinate development on shared goals.
- Be required to manage large technical projects from discovery to delivery.
- Manage, train, and develop a small group of engineers on your team.
- Help recruit and retain top engineering talent for the Automation team.
Ideal candidate has strengths with:
- Building scalable and fault-tolerant distributed systems that process large amounts of data
- Handling batch and event data for geospatial data and machine learning systems.
- Kubernetes clusters, workflows, management and tooling.
- Algorithms and data structures, domain-driven design, and event-based microservices.
- Familiarity with remote-sensing data such as satellite imagery, LIDAR, and radar.
- Working as a technical and management leader for a small, high-performing team.