Senior Machine Learning Infrastructure Engineer

As an ML Infrastructure Engineer, you will own the hardware and software stack that enables our scientists to simulate brain dynamics. You will bridge the gap between bare-metal hardware and high-level JAX code, ensuring our researchers have the computing power and stability required to push the boundaries of AI., * Cluster Management:Manage, maintain, and optimize our local high-performance compute clusters (Linux-based, NVIDIA GPUs). You are the owner of the hardware environment.

• Containerization & Orchestration:Design and manage robust containerized environments (Docker/Kubernetes) to ensure reproducible and scalable research workflows.
• Infrastructure Optimization:Maintain and evolve the core ML software infrastructure (Python/JAX codebase), focusing on efficiency, reproducibility, and scalability.
• Research Operations (MLOps):Execute and monitor large-scale model training and inference runs in close cooperation with research scientists.
• Technical Support:Provide hands-on hardware and software support to the research team, troubleshooting bottlenecks in the research workflow.

We are seeking technically proficient engineers with 5+ years of industry experience who love Linux and want to apply their skills to scientific discovery., * Education:M.Sc. in Computer Science, Engineering, Physics, or equivalent industry experience. Ph.D a plus.

• Experience: 5+ years of work experience with a proven track record.
• Linux Mastery:Deep expertise in Linux administration is non-negotiable. You must be comfortable managing clusters, users, and bare-metal hardware, shell scripting, and hardware configuration.
• Container Administration:Proven production experience with Docker and/orKubernetesis required. You know how to orchestrate complex workloads efficiently.
• ML Frameworks:Strong experience with Python and deep learning frameworks, specifically JAX and PyTorch.
• Bonus: Prior experience specifically inML Infrastructure administration(eg, Slurm, Docker/Kubernetes for ML).
• Bonus: Proventrack record of Open Source contributionsor personal software projects.
• Bonus: Experience incomputational modeling or neuroscience(understanding the "why" behind the code).

Soft Skills:

• Goal-driven and proactive:Strong self-management skills with the ability to take ownership of the infrastructure stack.
• Collaborative Mindset:A collaborative mindset; you enjoy enabling others to succeed.
• Communication:Excellent written and verbal communication skills in English. Knowledge of German is a plus, but not required.

• Impact:A unique opportunity to join an early-stage startup where your infrastructure decisions will directly shape the company's technological trajectory.
• Environment:A creative, interdisciplinary setting combining academic excellence with entrepreneurial spirit.
• Growth:Collaboration with international research partners and the chance to work on novel analog hardware concepts.
• Package:Competitive salary and benefits package.

At Noreja we rethink process mining and place the business objects along the process at the center of attention. Therefore, we focus on target- and user-oriented visualizations which provide direct implications for action. A new way to conduct data integration combines domain knowledge of process experts with process data – An approach we call Causal Process Mining.

Our software solution enables companies to leverage existing data from e.g., ERP, SCM, CRM, PLM or BPMS in order to transfer Business Process Management from subjective and time-consuming to data-driven and automated.

Our solution differentiates itself from other offerings because it is tailored to avoid spaghetti-like diagrams. Instead, the focus is on the causal relationships between events and actionable insights that provide opportunities for process optimization. To this end, we provide a solution for analysts to identify anomalies and optimization potential – without the need to understand process modeling notations or process mining specialties.