---
title: 'Applied AI Engineer at Fundamental'
canonical: 'https://feeny.ai/job/applied-ai-engineer-fundamental-europe-frcgd92v43ke'
type: 'job'
last_seen: '2026-09-16'
---

# Applied AI Engineer at Fundamental

- **Company:** Fundamental
- **Location:** Europe
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-05-20
- **Last confirmed live:** 2026-09-16
- **Apply:** https://jobs.ashbyhq.com/fundamental/9ce70592-8637-461f-b47c-6a1b47561461

## 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

- Take part in development and optimization of a large neural network-based tabular model implemented in Python
- Profile training and inference pipelines to identify performance bottlenecks
- Rewrite critical components in Rust (via PyO3 or custom extensions) where Python limits us, with C++ (via PyBind11 or custom extensions) as a secondary option where appropriate
- Improve memory efficiency, latency, and throughput across model pipelines
- Ensure correctness, numerical stability, and reproducibility as the model evolves
- Collaborate with ML researchers on productionizing new capabilities
- Maintain clean abstractions, comprehensive tests, and clear documentation
- Shape architectural decisions for our ML systems handling tabular data

Must have

- Strong software engineering fundamentals with expert-level Python and Rust
- Hands-on experience bridging Python and Rust (PyO3, maturin, or custom extensions)
- Experience developing and maintaining ML models in production
- Strong understanding of neural networks
- Track record of optimizing performance-critical code
- Strong profiling and debugging skills (CPU, memory, latency)

## Nice to have

- Experience with tabular ML approaches (transformers, tree/NN hybrids, learned embeddings)
- Working proficiency in C++ and experience bridging Python and C++ (PyBind11, Cython, or custom extensions)
- Familiarity with PyTorch internals or writing custom ops (Rust or C++)
- Experience optimizing training loops, data pipelines, or inference engines
- Background in numerical computing or systems programming
- Exposure to large-scale ML infrastructure (distributed training, batching, caching)
- Experience with the Rust async ecosystem (tokio) or SIMD/parallelism crates (rayon, ndarray)

## 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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