- Location
- Barcelona, Barcelona, Spain
- Employment
- Full time
- Level
- Mid level
- Posted
- 4 months ago
About this role
About Fundamental
Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS - the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
About the role
You will join the Engineering team as our first software engineer embedded within Research, owning the core codebase behind our model development. The codebase needs to be fast to iterate on, robust through experiments and large training runs, and ready to carry models all the way to production. Working alongside research scientists, you'll find what slows them down and build the infrastructure that fixes it, laying the technical foundations that let Fundamental operate at the frontier of large-scale tabular modeling.
Key responsibilities
Amplify and Accelerate: You will be proactive in providing solutions which enable our researchers to be more efficient and effective, including agentic workflows.
Steward: You will steward the long-term development and maintenance of our codebase. Ensuring it is production-ready, while preserving the flexibility needed for empirically driven research. You will set the bar for code quality by leading pull request reviews and acting as the gatekeeper for external contributions.
Champion Best Practices: Establish and implement software engineering best practices in the machine learning domain, serving as a mentor and guide to research scientists on the team.
Elevate Code Maturity & Quality: Lead the transition of our core research codebase from an early-stage experimental state to a highly scalable, maintainable and robust engineering standard. You will proactively manage technical debt, ensure experiment reproducibility, and drive overall code quality.
Maintain Documentation: Develop and maintain clear, comprehensive documentation for our research infrastructure and systems.
Collaborate Cross-Functionally: Ensure precise interactions of the research codebase with other code at Fundamental to translate research breakthroughs into tangible, real-world impact.
Guard the research - engineering contract: Build and own the testing layer that runs alongside model development: CI, contract tests, and verification that catch when research changes break the interfaces engineering depends on. Bugs should surface in PRs, not in production.
Must have
5+ years of software engineering experience, with meaningful time on ML or data-intensive backends, training pipelines, distributed inference, feature infrastructure, or similar.
Strong software architecture skills including modular design, clean interfaces, and design patterns for maintainable research codebases.
Excellent communication skills with a proven ability to discuss complex technical ideas clearly and collaborate effectively across interdisciplinary teams.
Expert-level proficiency in Python and deep familiarity with PyTorch.
Hands-on experience with the modern ML research tech stack and cloud infrastructure (e.g., cloud providers (AWS, GCP), Weights & Biases, Datadog, Kubernetes, ArgoCD, GitHub Actions).
Demonstrated track record of developing and utilizing solutions for robustness and quality assurance within software and/or ML systems.
Mission-driven mindset, motivated by the prospect of real-world impact and a relentless focus on excellence in software development.
Nice to have
Familiarity with MLOps best practices, CI/CD for machine learning, and infrastructure-as-code (e.g., Terraform).
Experience working in an early-stage, fast-paced startup environment.
A background or strong interest in tabular data, data engineering, or enterprise data architecture.
Experience with other programming languages (Rust, C++, Go)
Contributions to open-source machine learning libraries, frameworks, or tools.
Bachelor's degree in Computer Science, Software Engineering or a STEM field
Benefits
Competitive compensation with salary and equity
Comprehensive health coverage for you and your dependents
Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
As published by Fundamental. Applications are handled on their site.
Skills this posting mentions
About Fundamental
For decades companies have relied on archaic tools to inform decisions and make bets on the future. Until now. Fundamental empowers businesses to turn gambles into guarantees and determine their future with far greater accuracy than ever before. Built by DeepMind alumni and trusted by Fortune 100 enterprises, NEXUS is our most powerful Large Tabular Model (LTM). By revealing the hidden language of tables, NEXUS unlocks trillions of dollars of value by giving businesses the Power to Predict™.
All 23 openings at FundamentalOne click, then it is written
Apply to Fundamental with a resume written for this role.
Queue SWE, ML and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Fundamental’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
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Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
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