Senior AI R&D Engineer (Model Training)

Join our dynamic start-up as a Senior AI R&D Engineer in Model Training. You'll work across our full stack, optimizing training loads, enabling large-scale code execution for reinforcement learning, and improving inference throughput.

You'll co-own the training pipeline, build high-quality tooling, collaborate across disciplines, champion good engineering practices, and shape the direction of the team.

About Aleph Alpha

• Enjoy 30 days of paid vacation, flexible working hours, and the opportunity to work with international industry and science experts.
• Champion good engineering practices, working incrementally, maintaining fast feedback loops, and continuously refactoring to ensure long-term success.

Responsibilities

• Your work will directly impact our ability to experiment and improve our models.
• Co-own the training pipeline end-to-end, designing, building, and maintaining the infrastructure and components that allow for rapid experimentation and iteration on models.
• Collaborate across disciplines, working closely with engineers and researchers to learn from each other and iterate faster together.

Requirements

• Deep interest in how state-of-the-art foundation models work

Experience contributing in high-performing teams

• Desire to take ownership of problems and collaborate with other teams to solve them
• Strong communication skills, with the ability to convey technical solutions to diverse audiences
• Degree in computer science, engineering, or a related field
• Ability to write software that other strong engineers want to read and build on
• Willingness to relocate to Germany. Our primary working locations are Heidelberg (preferred) and Berlin, although there is some flexibility to work from other locations in Germany with regular travel to Heidelberg (potentially weekly)
• A track record of taking initiative to deliver high-impact work
• Experience working with distributed systems
• We do not require prior experience in machine learning for this role, but we do value your eagerness to learn. If you have prior experience in ML, we will be particularly excited about:
• Experience bringing AI research innovations into production
• Experience in areas such as large-scale data processing or distributed computation for foundation model training or inference

Preferred

• Experience working with Kubernetes
• Experience with performance engineering: profiling, benchmarking, and optimizing code for throughput, latency, or memory