About the Internship

Are you a passionate and curious engineering student looking for an opportunity to kickstart your career in AI? At Neuralk-AI, we're seeking a motivated intern to help us aggregate and structure training datasets by developing innovative web scraping pipelines. This is your chance to dive into the world of cutting-edge AI research while gaining hands-on experience in a dynamic startup environment!
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 in the Industry. Our focus is on developing a Agent based on Tabular AI to allow any company to build AI applications that natively interact with their structured databases (tabular).
• Specifically, we develop a modern AI workflows platform that automatically solve your use-cases with state-of-the-art performance without custom training on your data.
• As an early-stage AI-driven startup backed by significant funding ($4M), our AI-agent is powered by our proprietary Tabular Foundation Model, driving practical business solutions from research. 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) & 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 passion for our mission, learn quickly and believe you can contribute, we want to hear from you.

Mission Highlights

As a Data Science Intern, you’ll play a key role in building high-quality training datasets that fuel our AI models. By developing web scraping pipelines and consolidating diverse data sources, you’ll help lay the foundation for groundbreaking advancements in AI for structured data.

Role & Responsibilities

• Web scraping: Design, implement, and maintain efficient web scraping pipelines to collect high-quality data from diverse online sources.
• Data cleaning and preprocessing: Ensure the scraped data is accurate, structured, and ready for use in training AI models.
• Dataset consolidation: Aggregate data from multiple sources, standardizing formats and ensuring compatibility with our AI platform.
• Collaborative work: Partner with our research and engineering teams (~5 people) to identify the most valuable data sources and contribute to our dataset strategy.‍
• Exploration: Experiment with innovative approaches to improve data quality and diversity, fueling better model performance.

Minimum Qualifications

• Currently pursuing a degree in Computer Science, Engineering, Data Science, or a related field (Bac+3/Bac+5 or equivalent).
• Programming skills: Proficiency in Python; experience with web scraping libraries like BeautifulSoup, Scrapy, or Selenium is a big plus.
• Data processing: Familiarity with data cleaning and preprocessing tools (e.g., Pandas, NumPy, Skrub).
• Strong interest in AI and machine learning; curiosity about how structured data can be transformed into actionable insights (Sklearn).
• Self-starter with the ability to work autonomously and solve problems creatively.
• Good communication skills in English.

Preferred Qualifications

• Experience with large-scale data collection or analysis projects.
• Interest or experience in deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with version control systems like Git.

Why you should 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.