AI Research Engineer

OverviewJoin our AI Research Team in Milan to build the next generation of large language models, across the full life cycle: pretraining on trillions of tokens, state‑of‑the‑art post‑training, and releases spanning from a few billion to hundreds of billions of parameters.You’ll collaborate directly with leading industry labs such as NVIDIA, and your work will ship into mission‑critical deployments with some of the largest players in banking, defence, manufacturing, and the public sector.You’ll have first‑class access to our proprietary sovereign HPC, powered by NVIDIA Blackwell GPUs and designed for frontier‑scale model training, alongside additional allocations on European HPC infrastructure.As an AI Research Engineer, you’ll sit at the intersection of research and production, designing and optimizing the infrastructure that trains and serves these models. Expect to touch every layer of the stack, and contribute to open‑source projects shaping the European AI ecosystem.ResponsibilitiesCollaborate with industry labs and ship models into deployments across banking, defence, manufacturing, and the public sector.Design and optimize the infrastructure that trains and serves trillion‑parameter models, touching every layer of the stack.Contribute to open‑source projects shaping the European AI ecosystem.Implement advanced training techniques, including low‑precision training, quantisation, pruning, and distillation at scale.QualificationsPhD in Computer Science, Artificial Intelligence or a related field, or practical experience equivalent to a PhD.At least 5 years of proven experience as an AI research engineer, or PhD candidate with more than 2 years of experience.Expertise in modern machine‑learning frameworks such as PyTorch, TensorFlow, and JAX, with deep knowledge of distributed training using PyTorch Distributed, Ray, and DeepSpeed.Proficiency in Python and C++ or Rust for high‑performance inference and AI accelerators.Solid understanding of mathematics behind deep learning (linear algebra, probability, optimisation).Track record of publications at top‑tier AI venues.Contributions to open‑source AI projects demonstrating systems‑level thinking and impact in the research community.Experience with low‑precision training (FP8, FP4), quantisation, pruning, or distillation at scale.Fluent in English.Desired AttributesVersatile engineer comfortable operating across both research and production environments.Systems thinker who thrives at the intersection of research and engineering, optimising infrastructure for trillion‑parameter models.Collaborative team player, enthusiastic, curious, and adept at problem‑solving, capable of working independently and in a team.Motivated by building scalable AI systems with real‑world impact.Benefits & PerksTraining budget for books, online courses, or other learning materials.Option to work from home.Compensation reviewed in line with impact and experience.Employment TermsEmployment terms are governed by the CCNL Commercio, the Italian National Collective Bargaining Agreement for the Commerce, Distribution and Services sector. #J-18808-Ljbffr