Full Stack Engineer, Scientific Modeling Tools

About the role

Terra AI is building a new category at the intersection of artificial intelligence, geoscience, and critical resource development. The role focuses on productionizing and extending internal modeling tools used to generate subsurface outputs, taking software built around scientific workflows and making it robust, maintainable, and easier to run, inspect, and extend. You will own the durable foundation for multiple scientific domains, including geophysics and reservoir simulation, while collaborating closely with domain experts to translate requirements into software that is correct, usable, and extensible. This position requires a strong blend of product-quality engineering and scientific computing, where you will design APIs, improve testing strategies, and enhance developer experience without inventing new ML methods yourself. The work is deeply impactful, directly supporting the global energy transition by accelerating discovery timelines and reducing exploration risk for critical resources like copper, lithium, and rare earth elements.

Key facts

What you'll do

Collaborate closely with domain experts to translate requirements into software that is correct, usable, and extensible for subsurface modeling workflows.

Own and improve internal modeling stacks by refactoring and modularizing code for clarity and reuse across scientific teams.

Design and implement robust APIs and interfaces that turn working examples into maintainable components integrated into production systems.

Build configuration management patterns that ensure simulation runs are reproducible, debuggable, and traceable across complex workflows.

Implement and maintain orchestration pipelines for simulation ensembles and data validation, streamlining execution and monitoring.

Implement testing strategies tailored to scientific software realities, including golden tests, invariants, and property-based testing where useful.

Perform performance profiling and optimization focused on critical paths in scientific modeling tools to meet demanding computational needs.

Work primarily in Python and Julia, integrating with ML-adjacent components and artifacts such as inputs, outputs, and model wrappers.

Document and improve developer experience, ensuring that internal modeling stacks are accessible and sustainable for long-term use.

Support integration with existing geophysics and reservoir simulation tooling, maintaining compatibility and reliability in diverse environments.

Contribute to the design of data pipelines that handle large, complex datasets typical in mining and subsurface evaluation contexts.

Maintain and extend scientific modeling tools that reduce exploration risk and accelerate discovery timelines for strategic resources.

Ensure software components are aligned with Terra AI's mission to define a new global standard for data-driven critical resource development.

Requirements

Strong software engineering fundamentals and proven ability to take ownership of complex codebases in scientific and engineering domains.

Production-grade Python skills with experience building maintainable, testable, and performant code for data-intensive applications.

Comfort working in Julia or a demonstrated willingness to go deep quickly in scientific computing environments.

Experience designing APIs, handling configuration, and building reliable execution paths for complex workflows that span multiple software components.

Familiarity with performance profiling and optimization tooling to identify bottlenecks in scientific and data-intensive workloads.

Familiarity with ML frameworks at an integration level, with PyTorch preferred, and TensorFlow or JAX also relevant for model artifacts and runtime concerns.

Experience with orchestration or workflow tooling such as Flyte, Prefect, or Dagster, or equivalent patterns built in-house for scientific simulations.

A strong commitment to continual learning, candid communication, and environmental stewardship in support of modern exploration teams.

Nice to have

Geophysics or geomodeling experience, including survey simulation or related tooling such as SimPEG or similar frameworks.

Reservoir simulation experience with platforms like Eclipse, Intersect, or JutulDarcy used in critical resource evaluation.

Experience solving PDE-based problems in HPC environments, including familiarity with high-throughput computational workflows.

Familiarity with Fortran or C++ codebases common in scientific and engineering stacks that interface with legacy modeling tools.

Experience in simulation, CAD, or CFD domains within engineering or scientific software contexts.

Experience supporting scientific users and workflows where communication, clarity, and shared language are essential for successful collaboration.

Experience with batch pipelines and data-intensive systems that manage large volumes of subsurface and exploration data.

Practical notes

This is a full-time US remote position. No specific hours, travel, visa, or application deadlines are stated in the available source information.