SWE, ML
Fundamental4 months ago
Barcelona, SpainSenior
Responsibilities
- Build tools and workflows that improve research scientist productivity, including agentic workflows.
- Own the long-term development, maintenance, architecture, and production readiness of the research codebase.
- Establish software engineering best practices for machine learning and mentor research scientists.
- Mature experimental research code into scalable, maintainable, robust engineering systems while managing technical debt and experiment reproducibility.
- Develop and maintain documentation for research infrastructure and systems.
- Collaborate across teams to connect research code with other Fundamental systems and translate research into production impact.
- Build and own CI, contract tests, and verification systems that detect research-related interface breaks before production.
Requirements
- 5+ years of software engineering experience, including meaningful work with ML or data-intensive backends, training pipelines, distributed inference, feature infrastructure, or similar systems.
- Strong software architecture skills, including modular design, clean interfaces, and maintainable design patterns.
- Excellent communication and interdisciplinary collaboration skills.
- Expert-level Python proficiency and deep familiarity with PyTorch.
- Hands-on experience with modern ML research technology and cloud infrastructure, including tools such as AWS, GCP, Weights & Biases, Datadog, Kubernetes, ArgoCD, and GitHub Actions.
- Demonstrated experience improving robustness and quality assurance in software or ML systems.
- Familiarity with MLOps, CI/CD for machine learning, and infrastructure as code such as Terraform is preferred.
- Experience in an early-stage startup, tabular data, data engineering, enterprise data architecture, or open-source ML contributions is preferred.
- Experience with Rust, C++, or Go is preferred.
- A bachelor’s degree in Computer Science, Software Engineering, or a STEM field is preferred.
Benefits
- Competitive compensation with salary and equity.
- Comprehensive health coverage for employees and dependents.
- Paid parental leave for all new parents, including adoptive and surrogate journeys.
- Relocation support for employees moving to one of the company’s office locations.
- Mission-driven, low-ego culture valuing diversity of thought, ownership, and bias toward action.
Tech Stack
Categories