About the job offer
Neuralk-AI is looking for an AI Scientist with experience in AI model design and training.
You must have a PhD to apply.
You will report to the CSO of Neuralk and will be located in our Paris offices.
About Neuralk
We are a passionate team leading the way in AI innovation, committed to driving the rapid adoption of transformative AI applications. Our focus is on developing the technical tools to allow any company to build AI applications that natively interact with their structured databases (tabular or graph databases). Specifically, we develop a modern AI embedding platform to convert any structured database to a vectorstore that can later be combined with classic machine learning models for classification, regression or clustering purposes.
As an early-stage AI-driven startup backed by significant funding (several millions), we base our approach on state-of-the-art academic research to drive practical business solutions. We value clear communication and simplicity in our approaches, promoting a constant optimization mindset.
Join Neuralk to be part of a growing team, eager to learn and adapt, united by the belief that our technology can make a significant positive impact and contribute to transforming the AI industry.
Co-founders: Alexandre Pasquiou (CSO) and Antoine Moissenot (CEO)
Neuralk is dedicated to equal opportunity employment and fosters an environment that is open and respectful of diversity. All applicants are encouraged to apply. If you have at least 3 years of expertise, a passion for our mission, learn quickly and believe you can contribute, we want to hear from you.
Mission Highlights
As a Machine Learning Researcher, your role will be to improve in-house AI embedding models for structured data representation and translate them into actionable insights for strategic applications, which you will develop with our industrial and academic partners. You will collaborate closely with our engineering team (~7 people) to enhance the performance, scalability and impact of our AI-driven solutions, while also engaging with clients to answer their needs and deliver easily adaptable pre-trained embedding models.
Role and Responsibilities
By contributing to the core of our embedding platform, this position directly supports the company’s mission of making AI accessible and useful. You will be responsible for:
- Algorithms: contribute to the development of machine learning models for structured data representation in collaboration with dedicated teams
- Evaluation: continuously evaluate and optimize the performance of our ML 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 design and consolidate training and evaluation datasets to optimise representational and transfer learning abilities
- Research: stay current with the latest ML advancements and suggest optimisations to improve model performance and capabilities
- Pitching and communication: present 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 representation algorithms for downstream applications
- Ad-hoc analyses: run analyses to understand learning mechanisms of the foundation model, and work on the decodability of the embedding space
Profile
- PhD in computer science, machine learning, or a related field with a focus on deep learning
- 3+ years of experience in machine learning and software engineering roles involving training, fine-tuning, and evaluating deep learning algorithms (GNNs, Transformers) in the cloud
- Strong experience in training ML models and designing new learning paradigms
- Excellent communication skills in English
- Proven ability to work with interdisciplinary teams
- Thrives in a fast-paced, evolving startup environment
- Self-starter and autonomous
- Strong analytical and problem-solving skills
- Appetite to explore, implement new ideas and innovate
Bonuses
- Publication record in top-tier ML conferences or journals
- Experience designing and running large-scale ML experiments
- Demonstrated ML experience through open-source activity or data science competitions
- Track record of translating research into business impact
- Experience in developing and debugging in C/C++ and Python
Expertise
- Machine learning: deep understanding of ML theories and practices, especially related to reproducibility and scalability
- Embedding models: experience designing, training and evaluating embedding models
- Programming: proficiency in Python and ML frameworks (e.g. Sklearn, PyTorch, JAX); familiarity with Git and software engineering best practices
- Data management: familiarity with data structures and databases (Parquet, SQL, NoSQL)
- AI platforms: experience with model deployment and management; knowledge of Docker, Kubernetes, Pytorch
Compensation and Benefits
We are a fast-paced startup, yet we favor a good work-life balance and attractive compensation. We offer:
- A competitive salary
- Equity (BSPCE), reflecting the value you bring to Neuralk
- Comprehensive health insurance
- French-level paid leave and time off
- Dynamic work setting — we prefer in-person collaboration, but are flexible with occasional remote work
- And more to come as we grow
Interested in the role?
Get in touch and we will get back to you shortly.
