About us
We are building a new kind of AI. Not another deep learning system retrained every few months on yesterday's data, but a continuously learning architecture inspired by biological neural principles. Our systems adapt online, learn from single observations, and keep improving in production without catastrophic forgetting.
Our technology applies to any domain where the world changes faster than models can be retrained: energy markets, industrial systems, financial time series, health signals, and more. We are actively working across several of these, with our first commercial product live in the European energy sector.
We are a small founding team of engineers and researchers in Düsseldorf and Hamburg. We ship real software to real customers, and we publish honest thinking about where machine learning is going next.
The role
We are hiring a Software Engineer at the entry level. You will be the person who makes our systems run in production: reliable data ingestion from a growing set of external sources, pipelines that do not break at 3am when an upstream API changes, and the monitoring and tooling that lets us trust our own software.
Working at a deep-tech startup means you will sit between research and operations. On one side, our co-founders and lead research engineer are building a novel learning architecture. On the other side, real customers are making real decisions based on what our system outputs. Your job is to make sure the bridge between those two worlds holds up.
This is a backend-heavy role. You will touch ML systems every day, but you will not spend your time training models. You will spend it making sure the surrounding machinery is solid enough that the models can do their work, across multiple use cases as we grow.
You will learn a lot, quickly. We will invest in you.
What you will do in your first year
- Own the data ingestion layer across our product lines, starting with European electricity market data and extending to the other sources our systems depend on
- Build and harden the pipelines that feed our forecasting and learning systems with clean, validated, timely data
- Work on our distributed Ray-based execution layer: deployment, observability, actor lifecycle, performance profiling
- Build internal tooling for inspecting system behaviour on live and historical data
- Help us move from research prototypes to production services across new domains as we take on new use cases, and take ownership of specific subsystems over time
- Set up and maintain the CI/CD, testing, and monitoring practices that let a small team ship confidently
What we are looking for
Required
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related field (recent graduates welcome)
- Strong Python. You have written more than coursework in it and you know the difference between code that runs and code that ships
- Solid fundamentals in backend engineering: REST APIs, relational databases, testing
- Spring Boot experience (or experience anywhere in the JVM ecosystem)
- Comfort with Linux, Git, and the standard scientific Python stack (NumPy, Pandas)
- Fluent English, written and spoken. German is a plus but not required
We will be more interested if you have
- Experience building and operating data pipelines, ETL systems, or anything that ingests external APIs in production
- Familiarity with Ray, Dask, or similar distributed Python frameworks
- Experience with Kotlin
- Interest in machine learning systems, even if you have not yet worked on them professionally. We will teach you our architecture; we need you to be curious about it
- Exposure to any domain where data correctness and timeliness directly affect outcomes: energy, finance, industrial systems, health, or others
- Open-source contributions, a technical blog, or other evidence that you build things because you want to
What we care about beyond the CV
We care that you read code carefully, that you question assumptions including your own, and that when something breaks at 4pm on a Friday you are the kind of person who wants to understand why. We are a small team and personal ownership matters more to us than specific prior job titles.
What we offer
- Competitive salary in the range of €52,000 to €62,000 depending on experience, plus participation in our virtual share option program
- Hybrid working from our Düsseldorf or Hamburg office, with flexibility on days in the office
- 30 days of vacation plus public holidays
- Hardware of your choice within reason
- Structured mentorship from day one. You will have a weekly one-on-one with a co-founder and daily access to our lead research engineer. We invest in our people because we need them to grow fast
- A real first project. You will own a substantial piece of infrastructure within your first six months, not shadow someone else's work
- Direct exposure to the full stack of a deep-tech startup: architecture, product, customers, and the machine learning systems behind it all
How to apply
Send us a CV and a short note, in English or German, telling us what you have built that you are proud of. Links to code, papers, or projects are worth more to us than cover letters.
Apply to: careers@elysium-intellect.ai
We read every application ourselves.
Elysium Intellect is an equal opportunity employer. We hire on the strength of what you can do and how you think.
