---
title: 'ML Researcher at Fundamental'
canonical: 'https://feeny.ai/job/ml-researcher-fundamental-barcelona-g4qjp5n0hnnd'
type: 'job'
last_seen: '2026-09-09'
---

# ML Researcher at Fundamental

- **Company:** Fundamental
- **Location:** Barcelona, Spain
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-10-30
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/fundamental/d8a40a07-9a78-43dd-a93f-52148dc45b2c

## Job description

## 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.

## KEY RESPONSIBILITIES

As part of the Research team, you will contribute to ideation, designing, implementing, and evaluating breakthrough Machine Learning models that will be deployed in the real world. Your work will be focused on the entire lifecycle of the models. Alongside the rest of the ML researchers in the team, you will be responsible for our models’ performance in every meaning of this word - whether this means achieving high evaluation scores through novel architectures and training methods, establishing the evaluation protocols themselves, or implementing methods that allow for efficient training and inference. The greatest research is done through solid engineering, so alongside the research you will also take part in ensuring that our research code allows swift, rapid development and testing of new ideas - both your own and the rest of the team’s.

## MUST HAVE

- Strong familiarity with the full research cycle in Machine Learning
- Strong fundamentals of software engineering
- Strong knowledge of Python, and its ML frameworks
- Experience with:
- Full lifecycle of AI model development
- ML infrastructure frameworks and tools
- Developing new ML methods, algorithms and models
- GPUs (or TPUs) and distributed training
- Scaling up models and training regimes
- Knowledge of:
- Classical ML methods and algorithms
- Deep Learning techniques

## NICE TO HAVE

- Expertise within one of the following areas is a strong bonus: Architecture Research, Distillation (Model Compression), Evaluation, Code Generation, LLMs
- Experience with foundational models, e.g. LLMs
- Published research at AI conferences
- Contributions to open source ML projects
- Experience working with tabular data / predictive analytics
- High Kaggle rank
- BSc/MSc/PhD in computer science/machine learning

## 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

## About Fundamental

## Company Overview
- **One-liner**: Fundamental builds foundation models purpose‑designed for tabular data, enabling enterprises and governments to make accurate predictions and confident decisions.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Jeremy Fraenkel (CEO), Gabriel Suissa (Co‑Founder); built by DeepMind alumni

## Core Business
- Primary industry: Artificial intelligence / Enterprise AI (Large Tabular Models)
- Target customers: Large enterprises and government agencies (Fortune 100 clients)
- Mission: “To create a world of abundance by giving humanity the Power to Predict.”

## Products & Services
- **[NEXUS – Large Tabular Model (LTM)]**: A deterministic foundation model pre‑trained on billions of tables to ingest structured data (rows/columns) and capture complex, non‑linear feature interactions. Deployable with one line of code, integrates deeply with AWS, and designed for enterprise‑grade privacy and security. Unlike LLMs, NEXUS can reason over extremely large datasets (billions of rows) and provides consistent answers every time.

## Market Standing
- **Valuation/Market Cap**: $1.4 billion post‑money (as of February 2026)
- **Key Metric**: Total funding raised – $255 million (Series A: $225M led by Oak HC/FT, Valor Equity Partners, Battery Ventures, Salesforce Ventures; Angel round: $30M from investors including Perplexity CEO Aravind Srinivas, Brex co‑founder Henrique Dubugras, Datadog CEO Olivier Pomel)
- **Notable Investors/Partners**: Oak HC/FT, Valor Equity Partners, Battery Ventures, Salesforce Ventures, Hetz Ventures; strategic partnership with Amazon Web Services (AWS)
- **Growth Signals**: Emerged from stealth in February 2026 with seven‑figure contracts from Fortune 100 clients; headcount grew from founding to 46 employees with +28% monthly growth; operates globally (San Francisco, Barcelona, Israel, UK, etc.)

## Competitive Advantages
- **Deterministic & scalable**: Unlike transformer‑based LLMs, NEXUS is deterministic and can analyze tables with billions of rows without context‑window limitations.
- **Purpose‑built for tabular data**: Captures non‑linear feature interactions that LLMs miss, unlocking trillions of dollars in value from structured data.
- **Research‑led with academic rigor**: Team includes DeepMind alumni; model built on a non‑transformer architecture designed specifically for real‑world tabular data.
- **One model, many use cases**: Replaces armies of data scientists with a single foundation model that works across industries (finance, healthcare, energy, etc.).

## Strategic Focus
- **Expansion**: Deepening the AWS integration and scaling NEXUS across more Fortune 500/global government clients.
- **Talent acquisition**: Hiring across research (Barcelona), engineering (Europe, SF), and commercial roles (SF, Houston) to accelerate model development and go‑to‑market.
- **Category creation**: Pioneering the “Large Tabular Model” (LTM) category to differentiate from LLM companies and establish leadership in predictive AI for structured data.

## Why Work Here
- **Solve hard problems**: Work on groundbreaking research and engineering for a new modality of AI (tabular data) that most labs ignore.
- **Exceptional team**: Collaborate with DeepMind alumni and top researchers from Cohere, AI21 Labs, Google DeepMind, Mistral AI, and others.
- **Global and flexible**: Hubs in San Francisco (HQ), Barcelona (research), and remote‑friendly roles across Europe and the US.
- **Rapid growth**: Joining a well‑funded, high‑valuation startup at Series A stage with real revenue and Fortune 100 customers—clear trajectory.
- **Mission‑driven**: “Power to Predict” aims to transform decision‑making in enterprises and governments, offering tangible societal impact.
- **Culture**: Described as rigorous, ambitious, and supportive of deep research and patient engineering.

## Sources
1. [fundamental.tech](https://fundamental.tech/)
2. [fundamental.tech/company](https://fundamental.tech/company)
3. [fundamental.tech/careers](https://fundamental.tech/careers)
4. [TechCrunch - Funding announcement](https://techcrunch.com/2026/02/05/fundamental-raises-255-million-series-a-with-a-new-take-on-big-data-analysis/)
5. [LinkedIn Company Page](https://www.linkedin.com/company/fundamentalhq)

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