Descripción de la oferta
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, including medical, dental, vision, and 401K
Fertility support, as well as 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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