Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is 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 responsibilitiesAs 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 haveStrong 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
Expertise in at least one of the following:
Tabular models, time series models, relational foundation models, structured data, large-scale foundation models
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
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
Skills Required
- 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 the full lifecycle of AI model development
- Experience with ML infrastructure frameworks and tools
- Experience developing new ML methods, algorithms and models
- Experience with GPUs (or TPUs) and distributed training
- Experience scaling up models and training regimes
- Knowledge of classical ML methods and algorithms
- Knowledge of deep learning techniques
What We Do
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™.
