engineering
Posted Apr 20Software Engineer (All Levels), United Kingdom
United KingdomRemote
Responsibilities
- Building data pipelines and tooling for deriving advanced human and machine insights from exploration data, often leading a small group of software engineers to successful delivery
- A track record of taking ownership from definition of the problem and delivering projects with demonstrated impact in an iterative manner
Requirements
- KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs.
- At KoBold, software engineers have the unique opportunity to embed directly with their users and learn the ins and outs of mineral exploration and geology while developing state of the art technology solutions.
- As a Software Engineer on the Data Systems Engineering team at KoBold, your main role will be to enable systematic exploration and materially improve exploration success rates by making mineral exploration data broadly accessible to humans and machines. Past projects have included SIP (the Structured Ingest Pipeline), DataKit generation (producing curated sets of data on demand), and RAG (Retrieval Augmentation Generation, utilizing natural language processing on unstructured data).
- Our tech stack is primarily python and includes Django, React, AWS, and additional technologies like Retool and Prefect.
- Developing expertise in KoBold’s Data Systems and deeply understanding how they impact exploration
- Proficiency with Python
- Ability to write production-quality code that is correct, readable, well-tested, scalable and extensible
- Experience with modern frontend frameworks such as React •
- Experience with geospatial data and building map-based experiences
- Familiarity with containerization and container orchestration platforms, such as Docker, AWS ECS, Kubernetes, etc.
- Formal education or job exposure to natural sciences
Experience
- 4+ years of software engineering experience, ideally building production cloud data systems