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Innovative AI / ML engineer with around 10 years of delivering cutting-edge intelligent systems across SaaS, retail-tech, manufacturing and digital-health sectors. I specialise in architecting, building and operating generative-AI and large language-model platforms that empower automation, insight generation and strategic decision-making. Combining advanced research-led methods, modern MLOps practices and production engineering rigor, I create scalable, high-impact AI solutions that drive measurable business transformation.…Innovative AI / ML engineer with around 10 years of delivering cutting-edge intelligent systems across SaaS, retail-tech, manufacturing and digital-health sectors. I specialise in architecting, building and operating generative-AI and large language-model platforms that empower automation, insight generation and strategic decision-making. Combining advanced research-led methods, modern MLOps practices and production engineering rigor, I create scalable, high-impact AI solutions that drive measurable business transformation.

Felix Elsemann

AI Engineer, Data Scientist, Full Stack Developer, +3

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Innovative AI / ML engineer with around 10 years of delivering cutting-edge intelligent systems across SaaS, retail-tech, manufacturing and digital-health sectors. I specialise in architecting, building and operating generative-AI and large language-model platforms that empower automation, insight generation and strategic decision-making. Combining advanced research-led methods, modern MLOps practices and production engineering rigor, I create scalable, high-impact AI solutions that drive measurable business transformation.…Innovative AI / ML engineer with around 10 years of delivering cutting-edge intelligent systems across SaaS, retail-tech, manufacturing and digital-health sectors. I specialise in architecting, building and operating generative-AI and large language-model platforms that empower automation, insight generation and strategic decision-making. Combining advanced research-led methods, modern MLOps practices and production engineering rigor, I create scalable, high-impact AI solutions that drive measurable business transformation.

Available to hire

Innovative AI / ML engineer with around 10 years of delivering cutting-edge intelligent systems across SaaS, retail-tech, manufacturing and digital-health sectors.

I specialise in architecting, building and operating generative-AI and large language-model platforms that empower automation, insight generation and strategic decision-making. Combining advanced research-led methods, modern MLOps practices and production engineering rigor, I create scalable, high-impact AI solutions that drive measurable business transformation.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior AI / ML Engineer at Monterail

September 1, 2025 - September 1, 2025

Led design and deployment of a generative AI platform for a creative-services SaaS client, automatically producing multimedia content and highly personalized marketing assets for tens of thousands of concurrent users. Implemented a FastAPI-based microservices architecture, integrated recommendation and personalization modules, and built real-time event pipelines with Redis Streams and Celery to ingest, preprocess, and deliver interaction data to production ML models, reducing latency by over 45% and increasing throughput. Developed multilingual AI chatbots using OpenAI API and fine-tuned LLMs, enabling automated customer support for health-tech clients. Designed AI-powered analytics dashboards to surface key metrics and actions. Mentored engineers on prompt‑engineering, model operations and production serving, and established standardized AI workflows across teams.

Senior AI Developer

September 1, 2023 - September 1, 2023

Developed fraud detection and risk-scoring systems for large fintech clients using ensemble ML techniques and gradient-boosting models to improve detection precision while significantly reducing false positives. Built streaming data pipelines with PySpark and Kafka processing millions of events daily to support real-time underwriting and automated risk decisions for distributed microservices. Designed and implemented self-service MLOps pipelines with Airflow and GitLab CI/CD, automating training, validation, and deployment, improving pipeline efficiency and reproducibility across teams. Re-architected legacy monolithic backend into containerized microservices, improving scalability and reducing release cycle duration by roughly 50%. Implemented model monitoring dashboards and alerting for drift and anomalies, increasing reliability and maintainability. Collaborated closely with data science and DevOps teams to optimize cloud resource usage and integrate AI insights into production work

ML Engineer at MRPeasy

March 1, 2019 - March 1, 2019

Developed multilingual NLP-based support agents for small manufacturing clients, automating customer inquiry processing and internal support-ticket workflows, increasing operational throughput by 20%. Fine-tuned transformer-based LLMs using Hugging Face and PyTorch for real-time inference with minimal latency. Built monitoring dashboards with Prometheus and Grafana ensuring sub-300 ms inference latency and 99.9% uptime for production systems. Implemented real-time anomaly detection on industrial telemetry enabling predictive maintenance and reducing downtime. Delivered production-ready microservices capable of scaling in distributed cloud environments, collaborating with product and operations teams to integrate AI insights into manufacturing workflows.

Backend Developer at Agile

May 1, 2015 - May 1, 2015

Built backend systems for a global QA workflow platform, supporting high-concurrency enterprise operations with a stable, reliable infra. Developed automated test orchestration services using Redis and Flask, improving testing throughput by 30% and reducing scheduling delays. Integrated AI-powered bug triage modules based on NLP classifiers, reducing manual ticket sorting time by ~30%. Optimized PostgreSQL queries and implemented Redis caching strategies, reducing response latency by 25% under high-load conditions. Contributed to DevOps automation pipelines, streamlining deployment and integration processes across teams. Introduced code-review standards and documentation practices, improving maintainability and collaboration across teams.