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Data Research Engineer

Fundamental
Barcelona, Barcelona provincia

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Detalles del empleo

Jornada completa

Cualificaciones

Derecho
Doctorado
Informática
Spark
Máster
Machine learning
Deep learning
ETL
Python

Descripción completa del empleo

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

The greatest research is done through solid engineering. As part of the research team, you will contribute to development of breakthrough machine learning models by working on one of the most crucial aspects of ML model training: data. The main responsibilities of this role are:

Helping to identify, characterize and evaluate data sources, including realistic synthetic data generated from Structured Causal Models and physical / systems-based simulators
Building and maintaining ETL pipelines
Designing and implementing scalable, reliable data storage solutions
Collaborating with the rest of the research team to maintain a reliable, efficient training pipeline where data is a critical component
Collaborating with the wider engineering and infrastructure team

Must have

Experience with:
- Identifying good data sources to train and evaluate ML models, including real-world and realistic synthetic data sources
  Bringing data from structured and unstructured sources, as well as simulators and causal models, into formats accessible by ML models
Strong fundamentals of software engineering
Strong knowledge of:
- Python
- Python data processing stack (numpy, pandas, …)
Familiarity with:
- distributed processing (e.g. Ray, Dask Spark, Beam)
- data storage solutions
Basic ML knowledge

Nice to have

Contributions to open source ML projects
BSc/MSc/PhD in computer science/machine learning
Experience working with tabular data / predictive analytics
Experience working with "classical machine learning and deep learning" (pre-LLM)
Experience working with synthetic data generation, Structured Causal Models, or physical / systems-based simulators

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

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