‍About the Internship: Building AI Training Data and Benchmarks

Are you a curious and ambitious engineering or PhD student eager to gain deep expertise in AI? At Neuralk-AI, we're offering a unique opportunity to contribute to cutting-edge AI research by aggregating data, consolidating training datasets, and benchmarking state-of-the-art models. This internship is your chance to gain invaluable hands-on experience at the forefront of AI innovation while making a real impact in a dynamic startup environment!

About Neuralk

We are a fast-growing deeptech startup, leading the way in AI innovation. Our mission is to build a Foundation Model for Tabular data, enabling companies to create AI applications capable of interacting seamlessly with their structured data (tabular or graph databases). At the heart of our work is a modern AI embedding platform that transforms structured data into vector representations for applications in classification, regression, clustering, and more.

Backed by significant funding (>3M€), we combine state-of-the-art academic research with practical business applications to drive real impact. Our culture values simplicity, clear communication, and a constant drive for optimization.

At Neuralk, you’ll join a team of passionate individuals eager to learn, grow, and transform the AI industry. We believe in fostering a diverse, respectful, and inclusive environment and welcome candidates from all backgrounds to apply.

Co-founders: Alexandre Pasquiou (CSO) & Antoine Moissenot (CEO).

Reporting & Job Location

You will report to the CSO of Neuralk and will be located in our Paris offices.

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Mission Highlights

As a Research Intern, you’ll play a pivotal role in shaping the foundation of our AI models. Your contributions will help ensure that Neuralk stays at the cutting edge of AI for structured data. This internship provides a perfect blend of research and practical implementation, where your work will directly influence our model training and evaluation pipelines.

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Role & responsibilities

• Data Aggregation & Consolidation
  • Aggregate high-quality data from diverse sources to create robust training datasets.
  • Integrate training datasets into our training framework.
  • Develop tools and workflows to manage and monitor the quality and diversity of data.

• Model Benchmarking & Integration
  • Integrate and test existing state-of-the-art models within our benchmarking framework, comparing their performance on structured data.
  • Explore innovative approaches to enhance training efficiency and performance.

• Collaborative Research
  • Partner closely with Neuralk’s engineering and research teams (~5 people) to identify key challenges and opportunities.

• Contribute to internal discussions and brainstorming sessions that shape our R&D strategy.

Profile

• Educational Background:
  • Currently pursuing a Master’s or PhD in Computer Science, Data Science, AI, Engineering, or a related field.
• Technical Skills:
  • Strong programming proficiency in Python (e.g., Pandas, NumPy, Sklearn).
  • Experience with web scraping tools (e.g., BeautifulSoup, Scrapy, Selenium).
  • Familiarity with data preprocessing workflows and tools.
• AI Knowledge:
  • Interest in AI, particularly how structured data can be transformed into actionable insights.
  • Familiarity with machine learning frameworks like PyTorch.
• Soft Skills:
  • Strong problem-solving mindset with the ability to work independently.
  • Eagerness to experiment, learn, and contribute in a fast-paced environment.
  • Clear and concise communication in English.

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Extras that make you stand out

• Experience with large-scale data collection, integration, or analysis.
• Hands-on work with deep learning frameworks.
• Knowledge of version control systems like Git.
• Prior contributions to AI research or open-source projects.

Why join us ?

• Hands-on learning: Get practical experience in an exciting and rapidly evolving field.
• Mentorship: Work closely with experienced researchers and engineers who are eager to share their knowledge.
• Impactful work: Your contributions will directly support the development of cutting-edge AI models and platforms.
• Dynamic environment: Be part of a fast-growing startup where your ideas and efforts will make a tangible difference.
• Growth opportunities: Gain exposure to advanced AI concepts and methodologies, positioning yourself for a future career in machine learning.