Alborz Sabet
Platform Engineer with extensive experience leading technical development and deployment of machine learning solutions. Specializing in MLOps, I thrive on driving impactful projects from concept to implementation while ensuring compliance with industry standards. Through strong analytical skills, collaboration, and an adaptable mindset, I deliver scalable and effective AI solutions that align with strategic goals.
WORK EXPERIENCE
May 2024 – Current
Machine Learning Engineer
Udviklings- og Forenklingsstyrelsen, Copenhagen
  • Applied MLOPs principles on the government ML platform for advanced analysis
  • Implemented GDPR compliant RAG solution on company data
Nov. 2023 – May 2024
AI Engineer Team Lead
Senpage Consulting, Copenhagen
  • Led development of search engine and recommender system, greatly improving users connectivity, interaction and click-through rates
  • Set up in-house content-focused reference system, significantly increasing the accuracy of matching users as well as saving yearly cost by not depending on external services.
Dec. 2022 – Jan. 2023
Machine Learning Operations TA
DTU Compute, Lyngby
  • Provided mentorship and guidance to students on MLOps practices, emphasizing the importance of robust model deployment, monitoring, and maintenance.
  • Collaborated closely with faculty and research staff in troubleshooting, debugging and optimizing machine learning pipelines.
EDUCATION
Feb. 2021 – Sep. 2023
Msc - Autonomous Systems Engineering
Faculty of Electrical Engineering, DTU
  • Machine learning and Data Mining
  • Computer Vision and Image Analysis
  • Thesis: Automating video production using Deep Learning Approaches
Aug. 2016 – May 2019
BSc - Electrical Engineering
Faculty of Information-technology and Electronics, NTNU
  • Robotic Software Architecture
  • Control Systems Design
  • Thesis: Instrumentation and automation of an active Solar Tracker
TECHNICAL SKILLS
Python PyTorch CI/CD ELK-stack

Python

  • Expertise: Advanced (8+ years)
  • Applications: Built production ML pipelines processing 10TB+ data
  • Frameworks: NumPy, Pandas, Scikit-learn, FastAPI

PyTorch

  • Experience: 4+ years in deep learning
  • Models: Vision transformers, BERT variants
  • Current: Building GDPR-compliant RAG solutions

CI/CD

  • Platforms: GitLab CI, GitHub Actions, Azure DevOps
  • Impact: Reduced deployment time by 70%

ELK-stack

  • Scale: Managing logs from 50+ microservices
  • Use Case: Search engine analytics at Senpage
C++ OpenCV Azure Streamlit

C++

  • Focus: High-performance computing
  • Projects: Robotic control systems at NTNU

OpenCV

  • Expertise: Real-time video processing
  • Achievement: 95% accuracy in object detection

Azure

  • Services: Azure ML, AKS, Azure DevOps
  • Scale: 1M+ daily predictions

Streamlit

  • Use Cases: ML demos and dashboards
  • Impact: Created 15+ dashboards
HTML & CSS NLTK MLflow FastAPI

HTML & CSS

  • Frameworks: Bootstrap, Tailwind CSS

NLTK

  • Applications: Text preprocessing

MLflow

  • Implementation: ML lifecycle management

FastAPI

  • Performance: 10K+ requests/second
Javascript vLLM Kubernetes Terraform

Javascript

  • Frameworks: React, Node.js

vLLM

  • Purpose: High-throughput LLM serving

Kubernetes

  • Experience: Managing 20+ microservices

Terraform

  • Infrastructure: ML platform as code
OTHER
Merits
Norwegian boxing champion 2020-2022, Zealands boxing champion 2021-2023
DTU Robocup Runner-up 2022
Hobbies
Sports, Non-fiction reading, Philosophy
Languages
Norwegian, Danish, English, Spanish, Farsi