Senior AI Researcher- Pre-training (f/m/d)

Aleph Alpha

OUR MISSION Aleph Alpha is one of the few companies in Europe doing serious foundation model pre-training. Our customers - in finance, manufacturing, public administration - need models that understand German, meet European regulatory requirements, and work reliably in high-stakes settings. We're building that in Heidelberg. We're growing our pre-training team and hiring someone to passionately work on data: defining what goes into our models, building the systems that source and prepare it, and ensuring our training team has the highest-quality data to push model capabilities forward. Team Culture At Aleph Alpha, we foster a culture built on ownership, autonomy, and empowerment. Teams and individual contributors are trusted to take responsibility for their work and drive meaningful impact. We maintain a flat organisational structure with efficient, supportive management that enables quick decision‑making, open communication, and a strong sense of shared purpose. About the role As a Senior AI Researcher for Pre-training Data, you will shape and improve the underlying scientific methodology behind our pre-training corpora while also co-engineering the software and systems that enable this. Working with engineers and other researchers to build scalable pipelines, you will focus on relevant theoretical and empirical research required to understand which data makes models perform best on our targeted capabilities. This role is for you if you have a strong background in large-scale language modeling and the scientific drive to answer complex questions about data scaling laws, synthetic data generation, and curriculum learning. In your day-to-day, you will design targeted ablations across various scales, derive and test hypotheses from training dynamics, develop novel algorithms for estimating data quality and performing data curation, and contribute to a range of engineering tasks which facilitate these research directions. Together with a collaborative team of engineers and researchers, you will have a direct impact on the fundamental knowledge and capabilities of the models we ship. You will also help or lead the writing of technical reports for internal and external readers, as well as presenting at and contributing to technical meetings and conferences on an as-needed basis. YOUR RESPONSIBILITIES * Innovation in Data-Centric AI: Stay at the bleeding edge of foundation model research. You will identify, implement, and iterate on novel approaches to estimating data quality, synthetic data generation, curriculum learning, and advanced curation techniques. * Data-to-Performance Science: Design and lead rigorous ablation studies across various scales. You will systematically analyse how changes in data composition, deduplication strategies, heuristic and model-based curation, and scaling laws affect training dynamics and target model and system capabilities. * Develop Novel Quality Signals: Move beyond basic perplexity filtering. Research and build advanced algorithms to score and select data, such as influence functions, gradient-based matching, or using smaller models to curate data for larger ones. * Cross-Functional Collaboration: Partner closely with a diverse team to scale your research from prototypes to trillions-of-tokens-scale pipelines, and work with the post-training team to ensure pre-training distributions effectively support targeted fine-tuning and customer-alignment. YOUR PROFILE Basic Qualifications * A deep understanding of machine learning theory, specifically regarding foundation model training dynamics, scaling laws, and data-centric AI. * Experience designing and evaluating complex ML experiments related to data composition, curriculum learning, or data quality on language model training. * Familiarity with statistical methods for evaluation and experiment design. * Ability to reason about the information-theoretic properties of a dataset and its predictive power for evaluated tasks: not just processing data, but understanding its signal. * Strong Python skills and comfort with ML tooling and deep learning frameworks (especially PyTorch). * Willingness to relocate to Heidelberg or travel at least fortnightly. Preferred Qualifications * PhD in machine learning, NLP, or equivalent research experience focusing on large-scale language modeling or data curation. * A history of contributions to top-tier venues (NeurIPS, ICML, ICLR, ACL, etc.) specifically regarding data curation, scaling laws, synthetic data, or LLM pre-training. * Experience training foundation models from scratch and diagnosing data-induced training pathologies. * Bonus, but not required: German language proficiency can be helpful for curating and assessing German-language data. COMPENSATION AND BENEFITS * Become part of an AI revolution! * 30 days of paid vacation * Access to a variety of fitness & wellness offerings via Wellhub * Mental health support through nilo.health * Substantially subsidized company pension plan for your future security * Subsidized Germany-wide transportation ticket * Budget for additional technical equipment * Flexible working hours for better work-life balance and hybrid working model * JobRad® Bike Lease

Aleph Alpha

OUR MISSION Aleph Alpha is one of the few companies in Europe with end-to-end in-house model development including pre- and post-training. We’re building models that have general-purpose capabilities, but also specifically excel at addressing the needs of our customers. We're growing our post-training team in Heidelberg (or hybrid in Germany) and are looking for an AI Researcher who combines a deep theoretical understanding of reinforcement learning methods with a desire to improve on the state of the art and improve model capabilities in large-scale training. Team Culture At Aleph Alpha, we foster a culture built on ownership, autonomy, and empowerment. Teams and individual contributors are trusted to take responsibility for their work and drive meaningful impact. We maintain a flat organizational structure with efficient, supportive management that enables quick decision‑making, open communication, and a strong sense of shared purpose. ABOUT THE ROLE As a Senior AI Researcher for reinforcement learning you will shape and improve the underlying RL methodology, maintain a high-quality training code-base, and conduct large-scale experiments to hill-climb our performance benchmarks. This role is for you if you both have a strong theoretical background on RL and the engineering drive to bring these methods into production and improve on the methods as part of the reinforcement learning team. In your day-to-day you will conduct large-scale reinforcement learning experiments, derive hypotheses from the results, and iterate on both the implementation and methodology based on the observations. Together with a collaborative team, you will have direct impact on the models that we ship to our customers. This role is for Aleph Alpha Research GmbH. YOUR RESPONSIBILITIES * Hill-climb in large-scale training: Conduct large-scale LLM training runs, analyze evaluation scores in depth, propose hypotheses for improvement and directly implement them in order to maximize performance on our benchmarks. * Theoretical innovation: Stay at the bleeding edge of RL research. You will identify, implement, and iterate on novel approaches to multi-turn reinforcement learning. * Scale our training infrastructure: Identify bottlenecks in our training setup and optimize our RL training loops for large-scale training. * Cross-functional collaboration: Partner with our other post-training teams to turn raw feedback into actionable training signals, ensuring that our RL iterations lead to measurable improvements in downstream performance. YOUR PROFILE Basic Qualifications * A deep understanding of Reinforcement Learning theory and how it relates to modern RL methods. * Experience with multi-node LLM training (ideally using RL). You understand how to scale multi-node RL trainings and can reason about and implement distributed algorithms. * Familiarity with statistical methods for evaluation and experiment design. * Ability to reason about what an evaluation/environment measures and whether it matters - not just run benchmarks, but understand them. * Strong Python skills and comfort with ML tooling (especially torch distributed) * Willingness to relocate to Heidelberg or travel regularly (potentially weekly). Preferred Qualifications * PhD in reinforcement learning or equivalent research experience. * A history of contributions to top-tier venues (NeurIPS, ICML, ICLR, etc.) specifically regarding RL. * Experience evaluating LLM models and crafting environments for training. COMPENSATION AND BENEFITS * Become part of an AI revolution! * 30 days of paid vacation * Access to a variety of fitness & wellness offerings via Wellhub * Mental health support through nilo.health * Substantially subsidized company pension plan for your future security * Subsidized Germany-wide transportation ticket * Budget for additional technical equipment * Flexible working hours for better work-life balance and hybrid working model * JobRad® Bike Lease

Aleph Alpha

OUR MISSION Aleph Alpha is one of the few companies in Europe doing serious foundation model pre-training. Our customers - in finance, manufacturing, public administration - need models that understand German, meet European regulatory requirements, and work reliably in high-stakes settings. We're building that in Heidelberg. We are hiring a Senior AI R&D Engineer focused on Performance to grow our pre-training efficiency team. If you are excited about making models fast, this is the role for you! Team Culture At Aleph Alpha, we foster a culture built on ownership, autonomy, and empowerment. Teams and individual contributors are trusted to take responsibility for their work and drive meaningful impact. We maintain a flat organizational structure with efficient, supportive management that enables quick decision‑making, open communication, and a strong sense of shared purpose. ABOUT THE ROLE: You will engineer the systems required to train foundation models at scale. Your objective is to maximize hardware utilization and training throughput on our large-scale GPU clusters (thousands of NVIDIA Blackwell GPUs). You will work at the intersection of deep learning frameworks, distributed systems, and GPU microarchitecture, eliminating bottlenecks from the Python layer down to the GPU kernel. This role is for Aleph Alpha Research GmbH. Your responsibilities: * End-to-End Optimization: Profile training loops using PyTorch Profiler, Nsight Systems and Nsight Compute to identify system- and kernel-level bottlenecks in order to maximize model throughput. * Distributed Strategy and Topology: Configure and tune composite parallelism strategies (e.g. TP, DP, HSDP/FSDP, EP), optimizing load balance, minimizing critical-path bottlenecks, and managing communication-to-computation trade-offs for large-scale LLM training. * Hardware-Aware Modeling: Partner with AI Researchers to define model architectures for hardware efficiency without compromising convergence. YOUR PROFILE Basic Qualifications * Are proficient in Python and the PyTorch library. * Have a strong engineering background in parallel and/or distributed systems with proven track record of excellence. * Have hands-on experience with modern machine learning techniques (especially large language models and their life cycle). * Deeply understand the CUDA programming model. * Have experience in distributed programming with APIs like NCCL or MPI. * Have experience analysing profiling traces with tools such as PyTorch Profiler and Nvidia Nsight. * Please note this role requires regular on-site collaboration in Heidelberg as a member of the Training Efficiency Team. Preferred Qualifications * Contributions to modern distributed training frameworks (e.g., TorchTitan, Megatron-LM, DeepSpeed). * Familiarity with low-precision training formats (MXFP4, MXFP8) and their impact on numerical stability and throughput. * A deep understanding of NCCL communication primitives, NVSHMEM or CUDA IPC and their performance. * A proven track record of implementing and optimising modern transformer-based model training. * A proven track record working on the NVIDIA Blackwell architecture. COMPENSATION AND BENEFITS * Become part of an AI revolution! * 30 days of paid vacation * Access to a variety of fitness & wellness offerings via Wellhub * Mental health support through nilo.health * Substantially subsidized company pension plan for your future security * Subsidized Germany-wide transportation ticket * Budget for additional technical equipment * Flexible working hours for better work-life balance and hybrid working model * JobRad® Bike Lease