AI Scientist Paris 8, France

Neuralk-AI is looking for an AI Scientist with experience in AI model design and training.

You must have a PhD to apply.

You must have validated one of the following options below:

• you have pre-trained large transformer-based models -> pre-training team
• you have fine-tuned large transformer-based models -> fine-tuning team
• you have worked on model training and data distribution modelling -> synthetic data modelling team

You will report to the NicolaCancedda (VPResearch) and will be located in our Paris or London offices.

Neuralk is a deep-tech company building the next generation of Foundation Models for Data Science. Our mission is to build the predictive layer for businesses, transforming data science from a series of one-off initiatives, stitched together across silos, overly bespoke, and dependent on a handful of specialists, into a durable capability: a scalable predictive infrastructure that continuously learns from an organization’s data and powers decisions across the enterprise.

Our product is a Data Science agent, powered by our Foundation Models, that assists data scientists throughout their workflow, from problem framing to robust, production-ready models. We focus on the hardest and most common data problems in companies: structured datasets describing customers, operations, risks or financial activity.

As an early-stage, well-funded AI startup, Neuralk builds on state-of-the-art research to solve concrete business challenges. We value clarity over complexity, strong fundamentals over hype, and fast iteration grounded in rigorous engineering. Our ambition is to redefine how predictive AI is built and used in organizations, at scale.

Joining Neuralk means working hard in a fast-moving, research-driven environment, with a high level of ownership and the opportunity to shape a core product at the intersection of machine learning, engineering and real-world impact.

Mission Highlights:

As a Machine Learning Researcher, your role will be to contribute of the development of our foundation models for structured data (table and time-series). You will collaborate closely with our engineering team (~8 people) to enhance the performance, scalability and impact of our data science agent.

Role & Responsibilities:

By contributing to the core of our AI research effort, you will be responsible for:

• Algorithms: Contribute to the development of foundation models for structured data.
• Evaluation: Continuously evaluate and optimize the performance of our models by building adapted metrics reflecting the use-cases of our clients, building upon the insights from our industrial and academic partners.
• Active learning and training data optimisation: Participate in the active learning strategy and implementation process to improve sample selection and future model performance. As well as designing and consolidating training and evaluation datasets to optimise representational as well as transfer learning abilities of our Tabular Foundation models.
• Research: Stay current with the latest ML advancements in the field and suggest optimisations that may improve the foundation models’ performance and capabilities.
• Pitching & communication: present both ML research concepts to the scientific community and experimental design needs to the ML team.
• Collaboration: Work closely with ML engineers, data scientists, and clients to deliver promising representation algorithms for downstream applications.
• Ad-hoc analyses: Running analyses to understand the learning mechanisms of the foundation model.

Profile:

• PhD in Computer Science, Machine Learning or a closely related field, with a focus on deep learning.
• 3+ years of experience in machine learning which involved pre-training, fine-tuning and evaluating DL algorithms (Transformers) in the cloud or in a private cluster.
• You have a publication record in top-tier ML conferences or journals
• Excellent communication skills in English.
• Proven ability to work with interdisciplinary teams.
• Thrives in a fast-paced,