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I am a visionary Senior AI/ML Engineer with 10+ years of experience, specializing in end-to-end design, architecture, and deployment of enterprise-scale Generative AI and multi-modal AI solutions. I excel at translating research into scalable, high-impact applications across healthcare and fintech, and I am proficient in MLOps, LLMOps, and responsible AI practices.\n\nI have led and mentored globally distributed teams from ideation to production, delivering systems that meet stringent requirements for scalability, performance, and regulatory compliance across AWS, GCP, and Kubernetes. I combine strategic technical leadership with a hands-on, product-minded approach to bridge cutting-edge research and tangible business value.…I am a visionary Senior AI/ML Engineer with 10+ years of experience, specializing in end-to-end design, architecture, and deployment of enterprise-scale Generative AI and multi-modal AI solutions. I excel at translating research into scalable, high-impact applications across healthcare and fintech, and I am proficient in MLOps, LLMOps, and responsible AI practices.\n\nI have led and mentored globally distributed teams from ideation to production, delivering systems that meet stringent requirements for scalability, performance, and regulatory compliance across AWS, GCP, and Kubernetes. I combine strategic technical leadership with a hands-on, product-minded approach to bridge cutting-edge research and tangible business value.

Christoph Ulrich

AI Engineer, Data Scientist, AI Developer, +3

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I am a visionary Senior AI/ML Engineer with 10+ years of experience, specializing in end-to-end design, architecture, and deployment of enterprise-scale Generative AI and multi-modal AI solutions. I excel at translating research into scalable, high-impact applications across healthcare and fintech, and I am proficient in MLOps, LLMOps, and responsible AI practices.\n\nI have led and mentored globally distributed teams from ideation to production, delivering systems that meet stringent requirements for scalability, performance, and regulatory compliance across AWS, GCP, and Kubernetes. I combine strategic technical leadership with a hands-on, product-minded approach to bridge cutting-edge research and tangible business value.…I am a visionary Senior AI/ML Engineer with 10+ years of experience, specializing in end-to-end design, architecture, and deployment of enterprise-scale Generative AI and multi-modal AI solutions. I excel at translating research into scalable, high-impact applications across healthcare and fintech, and I am proficient in MLOps, LLMOps, and responsible AI practices.\n\nI have led and mentored globally distributed teams from ideation to production, delivering systems that meet stringent requirements for scalability, performance, and regulatory compliance across AWS, GCP, and Kubernetes. I combine strategic technical leadership with a hands-on, product-minded approach to bridge cutting-edge research and tangible business value.

Available to hire

I am a visionary Senior AI/ML Engineer with 10+ years of experience, specializing in end-to-end design, architecture, and deployment of enterprise-scale Generative AI and multi-modal AI solutions. I excel at translating research into scalable, high-impact applications across healthcare and fintech, and I am proficient in MLOps, LLMOps, and responsible AI practices.\n\nI have led and mentored globally distributed teams from ideation to production, delivering systems that meet stringent requirements for scalability, performance, and regulatory compliance across AWS, GCP, and Kubernetes. I combine strategic technical leadership with a hands-on, product-minded approach to bridge cutting-edge research and tangible business value.

Skills

Experience Level

Expert

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Language

German

Advanced

English

Fluent

Work Experience

Senior AI/ML Engineer at MantraCare

June 1, 2022 - October 1, 2025

Led the end-to-end design and deployment of MantraCare’s Unified AI Care Personalization Engine, integrating multimodal data (therapy transcripts, MSK assessments, chronic-care logs, and wearable metrics) into a hierarchical reasoning architecture with LangChain, LangGraph, and LlamaIndex. Architected and productionized a multilingual Hybrid RAG platform for mental-health triage and wellness coaching, combining Pinecone, FAISS, HNSW indexing, metadata-aware retrieval, and TinyBERT reranking to reduce non-grounded responses by 27% and increase content relevance by 12%. Optimized LLM inference using vLLM, PagedAttention, TensorRT, dynamic batching, and quantization — achieving 30% higher GPU utilization and 50% lower inference latency. Implemented an enterprise Generative Safety Layer for detecting hallucination, toxicity classification, and cultural-context validation, reducing unsafe or non-compliant responses by 45%. Developed distributed fine-tuning pipelines for GPT-4o and LLaMA

Senior Machine Learning Engineer at Sage Software Inc

July 1, 2019 - April 30, 2022

Architected end-to-end ML/NLP system for financial analytics, integrating text and image processing pipelines to automate document analysis and support internal decision-making tools. Built a BERT-based NER model using TensorFlow and spaCy to extract structured data from financial documents, reducing data errors from 11% to 2%. Implemented topic modeling and classification with Gensim and NLTK to categorize millions of financial records annually, increasing search relevance and enabling faster insights. Enhanced a computer vision pipeline with TensorFlow and OpenCV to process images in financial documents, integrating outputs with NLP modules for richer structured data. Established an evaluation and monitoring framework using Weights & Biases, tracking model performance and drift across NLP and CV components. Automated ML lifecycle with Kubeflow, Terraform, CloudFormation, and AWS EKS, reducing release cycle time by 30% and enabling modular, scalable pipelines.

ML Developer at Anyline

February 1, 2016 - June 30, 2019

Developed and accelerated on-device OCR and computer vision models using TensorFlow Lite and PyTorch Mobile, improving multilingual text recognition accuracy by 12% and reducing inference latency by 22% via quantization and pruning. Built an automated synthetic data generation pipeline producing 250k labeled samples using GAN-based augmentation and domain randomization, cutting annotation time by 70% and improving OCR robustness. Implemented a hybrid CNN–LSTM model for real-time character sequence modeling on mobile devices, enabling sub-100ms inference and achieving 95%+ accuracy. Enhanced TireBuddy by implementing real-time tire sidewall detection and DOT code recognition, improving recognition accuracy by 22% and enabling adoption by 40+ automotive partners globally.