Hello, I'm Jens

Member of Technical Staff at Liquid AI | Applied ML | Low-Latency VLMs

Jens Lücke

About Me

Who I Am

Ph.D. physicist turned AI engineer with deep expertise in High-Performance Computing. I work on applied ML and post-training for text and vision models, currently focusing on low-latency VLM projects for the e-commerce sector.

Outside of work, I compete in powerlifting - the kind of systematic, incremental progress that also defines how I approach engineering problems.

Skills & Expertise

Model Training

Post-training, LoRA fine-tuning, synthetic data generation

HPC & Systems

C, MPI, CUDA, distributed computing, Cerebras

AI Agents

ReAct prompting, tool use, multi-step workflows

RAG Systems

Vector search, GraphRAG, knowledge graphs

Work Experience

Member of Technical Staff

May 2026 – Present

Liquid AI

  • Part of the applied ML and post-training text and vision team
  • Focused on low-latency VLM projects for the e-commerce sector

AI Engineer

Jan. 2024 – Apr. 2026

Aleph Alpha

  • Improved VLM performance by >50% (60% → 90% accuracy) via LoRA fine-tuning and a novel synthetic data generation pipeline
  • Ran pre-training ablations for a 3B parameter German-language LLM on a Cerebras CS-3 cluster (4.4T token dataset)
  • Part of the post-training team, building an evaluation platform and environments for GRPO-based RL post-training
  • Built GraphRAG PoC achieving 25% precision improvement over vanilla vector search on a complex legal document corpus
  • Developed ReAct-style AI agents to automate multi-step document analysis workflows with custom tool integration

Ph.D. in Theoretical Physics

Oct. 2019 – Dec. 2023

Humboldt University Berlin

  • Designed and executed large-scale QCD+QED simulations on HPC clusters across Europe, managing thousands of distributed cores
  • Authored 5,000+ line C/MPI mass-reweighting module for openQxD, improving simulation efficiency by 15%
  • Built high-performance Python pipeline (NumPy, SciPy) processing terabytes of MCMC simulation output
  • Achieved 4x GPU speedup of the Dirac operator via CUDA at an NVIDIA-sponsored hackathon
  • Member of RTG2575; taught statistical physics, quantum mechanics, and linear algebra

Full publication list on Google Scholar.

Get In Touch

Email

Run this in Python, or click to copy:

"".join(["@", "je", "ecke", ".", "ns", "ai", "lu"][i] for i in [1, 4, 0, 6, 2, 3, 5])

Location

Berlin, Germany

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