Lead Machine Learning Engineer

MatthiasEgli

Portrait of Matthias Egli, Lead Machine Learning Engineer

I build data science systems that make it into production and stay useful there.

Based in Switzerland

MSc Engineering, Data Science

Experience

Lead Machine Learning Engineer

2026 — present

ti&m AG

Building and running machine learning projects, owning their architecture and MLOps. Responsible for technical recruiting.

PythonMLOpsRAGAzureArchitecture

Lecturer

2026 — present

Universität Luzern

Teaching two courses in the Master in Economics and Management: Data Science Toolkits and Architectures, and Unsupervised Machine Learning.

TeachingData ScienceUnsupervised Learning

Senior Machine Learning Engineer

2024 — 2026

ti&m AG

Ran data science projects from the first analysis through to running them in production. Designed and tuned retrieval-augmented generation architectures, in the cloud and on-premises.

PythonAzure OpenAIRAGFastAPIDockerMLOps

Professional Machine Learning Engineer

2022 — 2024

ti&m AG

Built and maintained software with machine learning in it, mostly for banking and finance clients.

PythonPyTorchMachine LearningDockerFastAPI

Software Engineer

2019 — 2022

Schindler Group

Built a web application used across the group to automate testing of elevator control software. Front end, back end, and the test suite around it.

Next.jsReactNode.jsExpressJenkins

Assistant Mobile Apps

2019 — 2020

Hochschule Luzern

Native iOS and Android work on the university mobile apps, including maintenance and App Store releases.

Selected Projects

Call Center Automation

SUISA · · Senior ML Engineer

Transcribes incoming call recordings and hands them to customer service as structured meeting notes. Speakers are separated and labeled, calls are summarized, and staff can see the status of each recording.

PythonDeep LearningAzureFastAPIPostgreSQLCI/CD
Impact
  • Speaker-separated transcripts
  • Summary drafted per call
  • Status visible end to end

Internal Azure GPT Assistant

Innosuisse · · Senior ML Engineer

An internal GPT-based chat assistant built inside the client Azure environment and fitted to their existing processes and IT. Designed, built, and deployed under strict data-protection requirements.

TerraformAzureOpenAICI/CDArchitecture
Impact
  • Runs in their own Azure tenant
  • Infrastructure as code
  • Built to strict data-protection rules

AI RAG Foundation

Raiffeisen Schweiz · · Solution Architect

The internal AI platform at Raiffeisen, now carrying more than six use cases and open to the whole bank. Built on a RAG foundation with an evaluation pipeline, answers that cite their sources, and automatic hyperparameter tuning.

PythonAzure OpenAIFastAPIMLOpsNLP
Impact
  • 12'000+ users, whole bank
  • 6+ use cases

On-Premise RAG Chatbot

Government Agency · · Senior ML Engineer

An on-premise RAG chatbot for sensitive government data. Fine-tuned open-source LLMs with hybrid retrieval on Elasticsearch, running entirely inside an air-gapped network.

PythonLLM Fine-tuningRAGElasticsearchCUDA
Impact
  • Fully air-gapped deployment
  • Hybrid retrieval system
  • Streaming chat interface

Sequential Recommender System

Hochschule Luzern · · Data Scientist

Next-purchase prediction for over 50'000 customers, learned from more than 13 million transactions. Transformer-based sequential models, with contrastive learning to stop the representations collapsing.

PyTorchTransformersMLOpsContrastive LearningFastAPI
Impact
  • 13M transactions modeled
  • Hourly model updates
  • Real-time similarity search

ReportGenie

Raiffeisen Schweiz · · Senior ML Engineer

Compiles financial reports with LLMs, drafting and then refining them. Wired together over REST across Spring Boot and Python services.

Spring BootKotlinPythonAzure OpenAIDocker
Impact
  • Reports drafted automatically
  • Spans four systems
  • Swappable LLM steps

Other Work

  • Wrote the tender documents for the public procurement of a secure AI platform for Swiss municipalities and cities. Defined the architecture and operating requirements for a multi-tenant private-cloud or on-premise system handling highly sensitive data, serving LLM, translation, transcription, and search under Swiss compliance rules.

    Enterprise ArchitectureSecurity ArchitectureMachine Learning
  • A multilingual RAG assistant on the public SUISA site. Built the chatbot front end and owned its integration and delivery, down to the streaming API behind it.

    Frontend ArchitectureRAGStreamingAzureCI/CD
  • A customer platform for a consumer-credit bank, built as microservices. React and Next.js on the front, Spring Boot services behind it, Kafka for events and Camunda for workflows.

    Next.jsReactSpring BootKafkaKotlin
  • Detects food trends in social media posts using named entity recognition, topic detection, and time series forecasting.

    PyTorchNLPTime SeriesDocker
  • Reads fencing technique from video using 2D pose estimation. Published as an IEEE conference paper.

    TensorFlowComputer VisionPose Estimation
  • Web application for automating tests of elevator control software, with JWT authentication against Active Directory.

    Next.jsReactNode.jsExpressCypress
  • Predicts temperature-related elevator door failures by mining log messages, using Apache Spark and deep learning.

    Apache SparkTensorFlowAzure MLPython
  • Native Android and iOS apps for university operations and student services.

    SwiftJavaAngularNode.js

Education

  • MSc Engineering, Data Science

    Hochschule Luzern ·

  • BSc Computer Science, AI & Visual Computing

    Hochschule Luzern ·

Publication