(MSc/PhD) AI Research Intern - LLMs, Causal Inference & Decision Making
Prosus is hiring a (MSc/PhD) AI Research Intern - LLMs, Causal Inference & Decision Making in Amsterdam, Netherlands. Level rates it ; you can apply on Prosus.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions OpenAI, Anthropic and Hugging Face among its tools and skills.
- Level classes it as an internship.
- Prosus has 10 other open roles on Level.
AI in this role
Who We Are
You've ordered dinner through Just Eat Takeaway. You've bought and sold on OLX. You've paid with PayU. Chances are, you've already used a Prosus company today.
We are Prosus, a global technology company powering some of the world's leading lifestyle ecommerce businesses. Every day, billions of people across India, Latin America, Europe and beyond use our products and services to buy, sell, pay, connect and discover.
Our AI-driven ecosystem spans 100+ companies across ecommerce, food delivery, fintech and experiences, serving billions of consumers worldwide. AI powers how we operate and innovate, with more than 60,000 active AI agents helping our teams build, scale and move faster. Through our investment team, we also back the founders and technologies shaping the future: From robotics and autonomous systems to synthetic biology and frontier AI.
Guided by our five values Innovation, Results, People, Impact, and Entrepreneurship, culture is our competitive advantage. We thrive with experimentation; we build, we test, we learn, we iterate.
Join us in shaping the future of technology at global scale.
What you'll do:
Build and experiment with LLMs, representation models, and modern ML systems for causal and decision-making problems
Work with large-scale experimental data to understand how users respond to different interventions
Build models for treatment effects, uplift, and counterfactual prediction
Design experiments, analyze randomized controlled trials, and evaluate results
Develop constrained optimization models for promotion and incentive allocation
Read research papers, prototype ideas, and turn the ones that work into real systems
Preferred qualifications & traits:
You're strong in mathematics, probability, and statistics and enjoy reasoning about problems formally.
You have strong quantitative modeling fundamentals, whether your background is in machine learning, economics, finance, operations research, statistics, or another technical field.
You understand causal and experimental reasoning and are comfortable thinking about RCTs, counterfactuals, treatment effects, and confounding.
You're interested in optimization and decision making, such as allocating limited resources, optimizing under constraints, or choosing actions under uncertainty.
You know how to write good Python code from projects, research, coursework, or similar experience.
You're comfortable with modern AI, including neural networks, representation learning, transformers, and LLMs, or have the technical background and interest to learn them quickly. Experience with PyTorch/JAX is a strong plus.
You can make sense of research by reading papers, understanding the key ideas, questioning assumptions, and turning them into working code.
You work well with others, are genuinely curious, and enjoy learning new ideas and technologies.
You're friends with AI assistants and use them regularly for coding, research, and writing.
You can commit to 6-12 months working with us in Amsterdam (minimum 3 days in the office weekly). We'll work with your academic schedule.
Experience with causal inference, econometrics, empirical economics, operations research, quantitative finance, uplift modeling, treatment-effect estimation, or mathematical optimization is a plus. This could include methods such as S/T/X-learners, causal forests, causal DAGs, potential outcomes, linear or integer optimization, Lagrangian/dual methods, stochastic optimization, or related techniques.
Prior experience with promotions, pricing, ads, recommendations, logistics, marketplaces, or other allocation and decision systems is a strong bonus, but not required.
What we offer:
Learn from the best: Work with AI engineers who've published at NeurIPS, released top models on Hugging Face, and built production systems at scale
Work on hard ML problems: Combine LLMs, causal inference, experimentation, and optimization in real-world decision systems
Unique data at scale: Access to billions of interaction logs from 500+ million users across our e-commerce platforms
Real infrastructure: Access to H200 GPU clusters, large-scale datasets, and all major LLM APIs (OpenAI, Anthropic, Google)
Ship real work: Prototype ideas, test them rigorously, and work toward systems that influence real product decisions
Grow your career: People who excel here tend to stick around
Junior Engineer compensation: We pay competitively for the impact you'll have
Best-in-class tools: MacBook Pro, access to major LLM APIs and premium coding assistants
Great workspace: Modern office in Amsterdam South with free barista coffee and NS travel card for your commute
This internship puts you at the intersection of modern AI, causal inference, and real-world decision making. If you like mathematics, experimentation, machine learning, and LLMs, and want to work on problems where models are used to make real decisions, we'd love to hear from you.
Eligibility:
This internship is open to candidates who are currently enrolled at a university and either hold EU citizenship or are studying in the Netherlands. We are unable to support visa applications for internships for candidates who do not meet these criteria.
Why Prosus?
At Prosus, your colleagues include 60,000 AI agents… and your job is to figure out what that actually means. We're one of the largest operators of agentic AI on the planet, inside a $100B+ portfolio across 100+ companies and two billion people. The humans here own what AI can't do alone: judgment, creativity, and the call on what gets built next.
Own the impact. Work the ecosystem. Earn your growth. Build with backing.
Curious about our perks and benefits? Take a look at this page.
Our Diversity & Inclusion Commitment
We respect the dignity and human rights of individuals and communities wherever we operate in the world. Building an inclusive workplace where everyone feels welcome and can thrive is critical for us. We provide access to education, which helps everyone understand the important role they play and the positive impact they can have.
Want to know more about life at Prosus? Explore our culture and values.
How we rate this
(MSc/PhD) AI Research Intern - LLMs, Causal Inference & Decision Making at Prosus rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a research question you investigated. What did you find?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Anthropic hands-on?
- Walk me through how you've used Hugging Face in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: AI agents, AI Research, OpenAI, Anthropic, and Hugging Face. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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