Axel Sneitz-Björkman
Machine Learning Engineer
About
Experienced Machine Learning Engineer with a strong foundation in full-stack development and a passion for creating impactful AI solutions. Proven ability to design, implement, and deploy machine learning models in real-world applications, with a focus on delivering tangible results. I like to build cool stuff that matters.
Work Experience
NordAxon
Machine Learning Engineer
Consultant role, working with both clients and in-house projects.
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INGKA - As part of GLS team, designed and implemented AI workflows for cross-translation language consistency.
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Tetra Pak - Built and evaluated BERT-based anomaly prediction model for manufacturing applications.
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Alfa Laval - Implemented air-gapped RAG platform for document Q&A using Streamlit, llamaIndex and Gotenberg.
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LindInvent - Developed anomaly detection for indoor climate systems using LSTM autoencoders on multisensor time series data.
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Emely Chatbot (Internal) - Full-stack conversational agent development including grammatical corrections, ASR evaluations and system architecture.
Advenica
Full Stack Engineer
Designed and developed the DD System Management Platform, enabling customers to manage scalable network segmentation in IT/OT environments. Supported AI-driven innovation by mentoring students writing their master's theses and served as an appointed DevSec specialist. Core technologies: TypeScript, React, Node.js, Docker, and gRPC.
EricssonInternship
Summer & Part-time Engineering Internship
Designed, protyped and manufactured modular, remote-controlled motion rig designed to automate testing-equipment placement within R&D Labs. Core tehcnologies: Python, Telnet and CAD
Education
Lund University (Lunds Tekniska Högskola)
Coursework: Computer vision, Image analysis, Applied Machine Learning, Stochastic Methods, Spatial Statistics, Cognition.
Voluntary Work
Lund Formula Student
Systems and Sensors Engineer
Skills
Side Projects
Laundry Booking System
Designed and deployed a Laundry-booking system for Lunds Nation serving 200 tenants with scalable technologies.
ISP Metrics
Small project measuring and presenting ISP metrics in a dashboard