# AI/ML Engineer at Riverlane

Riverlane is hiring an AI/ML Engineer. It pays €70k-€90k a year and Level rates it Builds AI ●●●●; you can [apply on Riverlane](https://jobsbylevel.com/go/0e188eea-3ae9-4fbe-9c5e-6e86184917a7?utm_medium=ai-agent).

AI Level 4, AI centrality 99 out of 100. Delft, NL.

## Details

- Company: [Riverlane](https://jobsbylevel.com/companies/riverlane)
- AI level: AI Level 4 (score 99 out of 100)
- Location: Delft, NL
- Salary: €70k-€90k
- Posted: October 28, 2026
- Apply: https://jobsbylevel.com/go/0e188eea-3ae9-4fbe-9c5e-6e86184917a7?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=ai-ml-engineer-at-riverlane-6e8782

## Prepare for this job

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## Description

AI/ML Engineer Delft, NL | Full-time | Permanent | Hybrid Salary: €70,000 to €90,000 DOE The salary range for this role is broad, as we are able to consider varying levels of experience. Any offer made will carefully take into account level of experience (including relevant industry experience), transferable relevant skills and previous relevant achievements. About us Riverlane’s mission is to master quantum error correction (QEC) and unlock a new age of human progress. From advances in material and climate science, to complex chemistry simulation for new drug design, quantum computers will help humanity solve some of its most important challenges. But without QEC, the industry’s defining technical challenge, such breakthroughs can never be achieved. Riverlane is the world leader in QEC technology. QEC is a complex problem that requires a range of skills, talent and passion. Having raised more than $125M in funding to date to accelerate our cutting-edge R&D in quantum error correction (QEC), Riverlane partners with many of the world’s leading quantum hardware providers and government agencies to make fault-tolerant quantum computing a reality. We’re making remarkable progress and growing fast. About the role As an AI/ML Engineer at Riverlane, you will apply artificial intelligence (AI) and machine learning (ML) to one of the defining challenges in quantum computing: quantum error correction (QEC). You will join our newly established R&D team in Delft, which focuses on using AI and ML to advance the state of the art in QEC and on deploying the resulting models in our QEC stack. As part of a highly collaborative research group, you will bring ML expertise and work together with QEC researchers to develop novel solutions at the intersection of these fields. You will build, train and test models on real experimental data, and where your impact comes through the quality of your engineering, your ability to turn ideas into working tools and your ability to collaborate with colleagues from a range of disciplines. You will tackle genuinely novel problems and help define how AI will shape the future of quantum error correction. What you will do In this role, you will apply your ML expertise and working knowledge of QEC to design, build and improve the AI models that power our next-generation QEC tools. You will collaborate closely with QEC researchers, other AI engineers and software engineers to turn promising ideas into intelligent, adaptive and scalable solutions. From early-stage prototyping through to training, optimisation and deployment, you will play a key role in taking AI models for QEC from research into production-ready technology. Your work will vary, but typical activities include: Design, train and evaluate ML models for QEC tasks such as decoding, calibration and noise characterisation, using both simulated and real experimental data. Build robust data pipelines and training infrastructure to support rapid experimentation and hyperparameter tuning. Optimise models for performance, latency and scalability, considering hardware and QEC constraints. Work with QEC researchers to identify promising ML techniques for QEC and translate them into practical prototypes and algorithms. Work closely with software, hardware and product teams to ensure research is grounded in real-world constraints and to integrate the prototyped models into Riverlane’s QEC stack. Communicate results clearly through technical write-ups and discussions and contribute to publications and conference presentations where appropriate. What we need An MSc or PhD in Computer Science, Mathematics, Physics or a related technical field (or equivalent professional experience). At least 2–3 years’ experience in machine learning, deep learning or other areas of artificial intelligence, gained in industry or academia (e.g. as a postdoc). Working knowledge of QEC, gained through research, projects or industry experience. Strong programming skills, preferably in

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