Full Stack Engineer, Scientific Modeling Tools

Job not on LinkedIn

🕒 January 23

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

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Terra

WebsiteLinkedInAll Job Openings

51 - 200 employees

📋 Compliance

☁️ SaaS

Insurance • Compliance • SaaS

Terra is a provider of cloud-native software solutions that simplify and enhance the management of Workers' Compensation claims and policies. Their platform streamlines operations through automated workflows, integrates with medical services, and offers robust analytics, helping users improve efficiency and ensure compliance. Designed for third-party administrators, insurers, and self-insured groups, Terra's solutions allow for effective claims handling and policy management without the burden of traditional legacy systems.

📋 Description

• 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 that match scientific software realities (golden tests, invariants, property-based testing where useful) • 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 that make runs reproducible and debuggable. • Implement and maintain orchestration pipelines for simulation ensembles and data validation. • Establish versioning and release practices for internal tooling, including metadata management. • Work primarily in Python and Julia. • Integrate with ML-adjacent components and artifacts (inputs, outputs, model wrappers), without being responsible for inventing new ML methods.

🎯 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.

🏖️ Benefits

• Competitive salary • Fully remote work opportunities • Flexible work hours • Professional growth and development