Senior AI R&D Engineer – Model Training (f/m/d)

Heidelberg · Remotefull time

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Remote

senior

H1B: no

Alephalpha The Senior AI R&D Engineer – Model Training at Aleph Alpha works on building and improving the model training pipeline for foundation models like Kolibri-1. The role involves full-stack work including optimizing training load scheduling, enabling large-scale code execution, and improving evaluation throughput.

Responsibilities

As an AI R&D Engineer in Model Training (f/m/d), you will join our model training team in Heidelberg or Berlin. Most of the team is based in Heidelberg. The model training team is building and improving our model training pipeline, which has been used to train Kolibri.
No two days are the same. Things move fast, and your ability to focus and prioritize is what lets you unblock the team day-to-day while designing the high-quality tooling and infrastructure that speeds us up long-term.
We're still building out our training pipeline and infrastructure. Some pieces exist, some do not, and you will have real influence on what gets built and how. Your work directly shapes how quickly we can experiment and improve our models.
Identifying issues and taking initiative is what drives our day-to-day work.
Working mode, design decisions, priorities are all done in your team together with your team mates.
The strongest teams often use highly collaborative techniques, like mob or pair programming.
Due to the highly collaborative nature of our work you are expected to be on-site at least two days a week. If you are in Berlin, you should expect to travel around every second month for a few days to Heidelberg.
We are specifically looking to strengthen the Software Engineering in the teams which are research heavy. Major points include improving the maintainability of our code through tests and design & architecture changes.

Qualification

At its coreTest Driven Development (TDD)Trunk based developmentContinuous integrationDomain Driven DesignMost of our code is in Python

Required

At its core, you need to be able to dive into a codebase, change the behavior as necessary, and after the change the code should be better tested and easier to understand than before.
As such we look for candidates for an understanding of how to design for low coupling and high cohesion paired with the ability to incrementally refactor.
Experience with the following technologies is likely to be helpful:
Test Driven Development (TDD)
Trunk based development
Continuous integration
Domain Driven Design

Preferred

Most of our code is in Python, there is also the occasional Rust codebase.
Large parts of our training pipeline are built on top of Kubernetes.
We do not hire for skills in a particular technology or language, but rather ability to learn and mindset, yet experience with these technologies is a plus.