Terra AI - Full Stack Engineer, Scientific Modeling Tools
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Requirements
• Strong software engineering fundamentals and proven ability to take ownership of complex codebases. • Production-grade Python skill. • Comfort working in Julia or willingness to go deep quickly. • Experience designing APIs, handling configuration, and building reliable execution paths for complex workflows. • Familiarity with performance profiling and optimization tooling. • Familiarity with ML frameworks at an integration level (PyTorch preferred, TensorFlow or JAX also relevant), including artifacts, I/O, and runtime concerns. • Experience with orchestration or workflow tooling (Flyte, Prefect, Dagster, or similar), or equivalent patterns built in-house. • Geophysics or geomodeling experience, including survey simulation or related tooling (SimPEG or similar). • Reservoir simulation experience (Eclipse, Intersect, JutulDarcy, or similar). • Experience solving PDE-based problems in HPC environments. • Familiarity with Fortran or C++ codebases common in scientific stacks. • Experience in simulation, CAD, CFD, or other engineering/scientific software domains. • Experience supporting scientific users and workflows, where communication and shared language matter. • Experience with batch pipelines and data-intensive systems.
Responsibilities
• Collaborate closely with domain experts to translate requirements into software that is correct, usable, and extensible. • Own and improve internal modeling stacks, including: • - Refactoring and modularization for clarity and reuse. • - Testing strategies matching scientific software realities (golden tests, invariants). • - Performance profiling and optimization where it matters. • - Documentation and developer experience improvements. • Design and implement APIs and interfaces that turn working examples into maintainable components. • Build configuration management patterns for reproducibility and debuggability of runs. • Implement and maintain orchestration pipelines for simulation ensembles and data validation. • Establish versioning and release practices, including metadata management. • Work primarily in Python with comfort working knowledge or willingness to learn Julia quickly. • Integrate ML-adjacent components without inventing new methods but understanding their integration level (e.g., PyTorch preferred). • Familiarity required: strong software engineering fundamentals, production-grade Python skills, experience designing APIs and handling complex workflows configurations, familiar with performance profiling tooling, knowledge of ML frameworks at an integration level.
Benefits
• Equity compensation is mentioned as part of the benefits package. • Paid Time Off (PTO) options are included among the listed perks and benefits. • Insurance coverage for employees is provided, which can include health insurance or other relevant policies not specifically detailed in this excerpt. • Perks such as remote work opportunities may be available to candidates based on their role's needs within Terra AI’s operations.
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