Hello, I am
Adam Łagoda
Machine Learning Engineer building robust, scalable AI systems at Ramboll Tech
I specialize in MLOps practices on Azure, designing intelligent RAG workflows and agent-based systems with an emphasis on reliability, evaluation, and trustworthiness. My background spans Deep Reinforcement Learning, computer vision, robotics, and embedded systems.
Experience
Machine Learning EngineerCurrent
Rambøll Tech · Aarhus, Denmark
July 2024 – Present
- AI Report Generation Platform — serving and helping to standardize Rambøll report writing workflows (Impact Assessment, Air Quality, Fire Safety, Compliance Strategy & Transactions); 1,100 users, 578 reports, ≥10% reduction in time-to-draft
- Engineered document ingestion pipeline: Azure Function web skill → Document Intelligence layout analysis → content-aware chunking → semantic field extraction → AI Search indexers
- Implemented multi-agent retrieval system; evaluated with MRR, NDCG, Precision@K & Recall@K
- Engineered Azure APIM solution: cross-regional round-robin load balancing & circuit breaker; OAuth & RBAC; extended Azure OpenAI quota
- RAG-based Document Search Platform — end-to-end full-stack RAG for 3 external clients; 6,500 documents (50–100 pages each)
- Leads global ML community calls — 550+ members, ~100 regular attendees
- Contributed to global company standard for LLM evaluation and agentic orchestration framework
- University supervision: 4 students (2 BSc, 2 MSc at AAU Esbjerg); BSc RAG project deployed to production
Student Assistant
Rambøll Energy · Esbjerg, Denmark
February 2023 – June 2024
- Co-maintained 17 internal Python packages for offshore wind structural engineering (monopile design optimisation, soil model preparation, structural damage ingestion to SQL with visualisation dashboard)
- Designed and trained ANN surrogate model for fatigue load interpolation — <1% relative error; prediction <1s vs >600 core-hours of cloud simulation
- Migrated legacy CSV-based I/O to per-analysis SQLite databases; queryable for ML interpolation based on sea position
- Built skill-matching MVP: cross-correlated employee skills, availability & team to surface the right person for a project
- Led internal AI Knowledge Sharing Network within a global business area — 260 members, 60 regular attendees
- Set up CI/CD on on-prem GitLab and GCP (Cloud Run, BigQuery, Vertex AI, Compute Engine)
Research Assistant
Aalborg University · Esbjerg, Denmark
December 2022 – November 2023
- R&D on digital twin and Virtual Reality for remote offshore inspections using Unreal Engine
- Built communication protocol bridging Unreal Engine simulation and ROS
Electronics Engineer
Robotics Start-Up (NDA) · Copenhagen, Denmark
July 2022 – December 2022
- Member of R&D team; electromechanical system design, parts sourcing and procurement
CAD Consultant
KAJA S.K. · Koszalin, Poland
September 2020 – May 2022
- Optimised welded chair designs in SolidWorks; decomposed frames into laser-cut and CNC-bent parts maintaining dimensional accuracy for KUKA robotic arm welding
Research & Education
Publication
Dynamic Reward in DQN for Autonomous Navigation of UAVs Using Object Detection
CoDIT'23 · Rome, Italy
DOI: 10.1109/CoDIT58514.2023.10284087
Hack the Climate — 2nd Place
WindEurope 2024, Bilbao — 48-hour hackathon hosted by WindEurope, Vestas, HUB Ocean & Microsoft. Built decision-support tool optimising turbine rain shutdown based on electricity price vs. blade erosion cost.
March 2024
M.Sc. Advanced Power Electronics
Specialisation in AI and Autonomous Systems
Aalborg University · 2022 – 2024
B.Sc. Applied Industrial Electronics
Specialisation in Cyber Security and Systems
Aalborg University · 2019 – 2022