Ofertes d'ocupació a Joko

• Nivell d'experiència---
• Tipus de contracteTemporal
• PublicadaNova

Teletreball . Python Machine Learning Office

At Joko, we help consumers shop smarter. Our mission is to revolutionize shopping—empowering people to find what they need, make informed decisions, and save money.

Founded in Paris, Joko is a tech company and certified B Corp with over 80 talents across Paris, Barcelona, and New York (and beyond). More than 4 million users already save money every day at 7,000+ merchants with Joko.

From cashback and automatic coupons to price alerts and carbon tracking, we keep expanding our products to make shopping smarter. We’re now building an AI-powered shopping assistant to help users find the best products by price, quality, and impact.

Having reached profitability in our core market, we’re now scaling globally — with a strong focus on the US.

It’s still day 1, come build the future of shopping with us!

This position will be located in Paris

🧪 Research at Joko

At Joko, we believe that today’s online shopping experience is fundamentally flawed. Our ambition is to disrupt it by enabling users to find their desired products in the smoothest way possible, to effortlessly compare all their characteristics, and to access transparent and clear information on both their price and environmental cost.

To achieve our goal, our research team tackles two main challenges:

• Building the universal product catalog : We are developing the world’s largest universal product catalog, bringing together all the products sold across e-commerce worldwide. This requires the ability to understand any web page in order to extract structured information, and to clean and standardize data from millions of heterogeneous sources in near real time. One of the biggest difficulties lies in scale: we must process hundreds of millions of products multiple times per day
• Developing the AI Shopping copilot: On top of this catalog, we are building an AI copilot that helps users navigate our product universe through natural conversation. This goes well beyond traditional RAG systems: it requires combining full-text and vector search across massive datasets, while leveraging LLMs to ensure an experience that is reliable, fast, and cost-efficient. We continuously iterate to improve search accuracy, reduce latency, and better capture user intent.
  
  

To meet these challenges, we rely on LLM-based methods. We have developed state-of-the-art approaches centered on fine-tuning relatively small models, striking a balance between performance and efficiency. Still, much research remains to further optimize resource usage, scale our systems to ever larger volumes of data, and explore new architectures that push the boundaries of what LLMs can achieve in large-scale e-commerce applications.

⚙️ What you’ll do

At Joko, our Machine Learning interns are considered full members of our engineering teams. We design internships to be deeply tied to real-world projects, ensuring that interns can have a tangible impact from day one.

For end-of-studies internships, our goal is not only to provide a meaningful learning experience but also to prepare interns for a smooth transition into full-time engineering roles at Joko after their internship.

You will have full ownership of your project and the freedom to orient your research direction based on your results and what you consider promising. Your ultimate goal will be to deploy your work in production and monitor its impact on hundreds of thousands of users. Exploration is at the heart of the internship: you will conduct experiments, literature reviews, and theoretical developments.

As a Machine Learning Research Intern, You Will Work With Our Engineering Teams To Maximize Your Impact, And You Will Work On One Of The Following Research Topics

• Improving the Universal Catalog Pipeline
• Enhance the performance and scalability of our LLM-based data processing pipeline
• Explore fine-tuning for specialized tasks and techniques to reduce model size (quantization, pruning, distillation)
• Develop rigorous evaluation methods, notably using LLMs as judges
• Improving Search in the Catalog
• Benchmark search techniques that combine full-text and vector search
• Explore using images to enhance search performance
• Identify and evaluate the most effective LLM-based embedding methods
• Improving the AI Copilot
• Benchmark and fine-tune models to improve both performance and latency
• Work on model optimization (size reduction, distillation, quantization)
• Establish rigorous evaluation pipelines
  

📌 Your Responsibilities

• Research: Formalize objectives, conduct literature reviews, design new algorithms, and collect/transform data for experiments.
• Exploration & Ownership: Orient your internship towards research directions you deem most valuable to users.
• Implementation, Deployment & Monitoring: With the support of the engineering team, integrate robust algorithms into production and monitor their real-world impact.
  
  

🔍 What we are looking for

Technical & Problem-Solving

You have solid programming skills, with experience in Python and Machine Learning frameworks, and you are eager to keep improving. As a problem solver, you combine strong analytical skills, creativity, and a taste for tackling complex challenges. You are also tech savvy, always curious about emerging technologies and attentive to the latest trends in the domain.

Mindset & Communication

You have an entrepreneurial mindset: you like challenges, you welcome feedback, and you strive every day to get better and reach excellence. You have strong communication skills, both written and verbal, and you are able to explain complex topics in simple words. You are fluent in English, both spoken and written, as we are expanding internationally soon (mastering French is not required).

Adaptability & Efficiency

You are a fast learner, comfortable in any technical environment and quick to adopt new technologies and practices. You value efficiency, making good use of productivity tools and delivering on time even in projects with many stakeholders. Finally, you have great attention to detail: you know the devil is in the details and have a natural talent for spotting flaws when they exist.

📚 Preferred Background

• Education: You are a graduate student in a Machine Learning master, from an engineering school, and looking for an end-of-studies internship.
• Experience: You have experience with research, from past internships or projects.
  
  

💎 Our perks

At Joko, we believe that flexibility and trust are essential. Our work environment reflects this through:

• Flexible remote: If you live in Paris, you can choose to work from our office or from home with no constraints. If you live elsewhere, we can provide access to a coworking space.
• Work from anywhere: Want to spend a month in Italy while working? Full-time employees can work from most countries in the world for up to 3 months per year → full-time only
  
  

On top of that, we offer plenty of perks (some for everyone, others only for full-time positions):

• A budget for remote work equipment
• A Swile card for meals (if you are based in France)
• Frequent team events and in-person gatherings every quarter 🎉
• Premium health insurance (Alan Blue, in France) → full-time only
• A ClassPass subscription to stay in shape wherever you are → full-time only
• …and much more, check the full list here!
  
  

🤝 Our hiring process

• Intro call: Quick screening with the Hiring Manager or a recruiter.
• Step 1 – Team interview (45 min): Conversation with two Joko team members (could include the Hiring Manager, people from the team you’d join, or colleagues from other teams).
• Step 2 – Role-specific assessments
• For non-tech roles: Take-home case study followed by a 45 min debrief. We assess both your output and how you think in real time. The exercise will be relevant to the role (e.g. analysis, strategy, or process design).
• For tech roles: Live technical interviews:
• Coding interview + System design interview
• For research internships, an additional round may involve analyzing and presenting a research paper
• Step 3 – Founders interview (45 min): Conversation with two of our founders.
• References: Up to five calls with former colleagues or managers.
  

☕ You may also be invited for coffee with team members to get a feel for our culture.