Matthias D.-Senior AI/ML Engineer · Research-to-Production · Protein Design, NLP, Retrieval & Agentic Systems
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Experience
Chief Technology Officer
Ordaos, Inc.
- Architected and shipped the in-silico side of Ordaos' 5-day protein iteration cycle, compressing the design-evaluate-refine loop to a weekly cadence.
- Shipped internal LLM-powered copilots for engineering and scientific workflows (retrieval-augmented; LangChain / LlamaIndex; pgvector).
- Own technical direction across deep learning, ML infrastructure, biological data systems, and production deployment; hands-on reviewer on model architecture, training pipelines, and releases.
- Lead a 9–12 engineer organization (Platform / ML / UX) through team leads; retained core engineering capability through a period of leadership transition.
- Designed and implemented a REST API over the single source-of-truth database; oversaw connectors to the Benchling and Kaleidoscope biotech cloud platforms.
Senior Vice President of Engineering
Ordaos, Inc.
- Stood up ML training and evaluation infrastructure enabling all production models to be trained and evaluated locally or in the cloud.
- Architected and oversaw implementation of the in-silico protein optimizer; built the proprietary biological database and dynamic feature store.
- Architected and implemented a distributed, cloud-based workflow execution system to autonomously run training / evaluation and protein design cycles; exposed as a REST API.
Director of Engineering
Ordaos, Inc.
- Formed the engineering organization (Platform / ML / UX structure that scaled through the SVP and CTO tenures); hired 6 engineers.
- Introduced agile, scrum, code review, and deployment practices adapted for ML epics; implemented prototype enabling pH-specific binding.
Data Scientist
Pfizer, Inc.
- Built and deployed semantic search and retrieval over hundreds of thousands of manufacturing deviation reports in a GxP-regulated (21 CFR Part 11) environment; reduced investigation time by 57% and enabled cross-site duplicate detection.
- Delivered results with the traceability, validation, and domain-expert sign-off required for regulated, auditable decision support over large private document sets.
- Implemented topic clustering on sentence embeddings with a TF-IDF baseline for text similarity and retrieval.
Principal Engineer
Ordaos, Inc.
- Designed and implemented the prototype deep learning system for protein generation; built the foundational data representation, model workflows, and deployment architecture from scratch.
Lead Developer / Technical Lead
Kextil, LLC
- Architected and shipped an enterprise task-oriented conversational agent (voice) deployed across aircraft MRO, oil & gas, medical device maintenance, manufacturing, and semiconductor verticals.
- Owned dialogue flow, NLU, task-oriented behavior, and backend integration with client infrastructure; reduced task completion time by ~40% through hands-free operation (customer-reported).
Co-Founder & Technical Lead
Agilingua, LLC
- Architected an embedded dialogue stack for edge and resource-constrained hardware supporting on-device NLU and dialogue management; licensed the SDK to 6 clients across automotive (Ford US/Germany, GM, German Auto Labs, SpeakWithMe), VR (Deloitte), and industrial field service (Kextil).
Research Associate
NTT Communication Science Labs
- Research on reinforcement learning for dialogue policy / agent decision-making and restricted-domain question answering; resulted in 2 Japanese patents and peer-reviewed publications.
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Information Technology, Automotive, Manufacturing, Aerospace and Defense, Energy, and Healthcare.
Business area experience
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Experienced in Information Technology, Product Development, Research and Development, Strategy, and Business Intelligence.
Summary
Senior machine learning researcher and engineer (PhD, Computer Science; 30+ peer-reviewed publications; 2 patents) with six years building deep learning systems for biological sequence and structure data. As founding technical hire and later CTO at Ordaos, designed the protein generation system and the in-silico platform behind a 5-day design-evaluate-refine cycle: protein language models, developability and property prediction, structure-conditioned generation, antibody optimization, and the database, feature store and workflow infrastructure behind them. Earlier work in NLP, semantic retrieval in GxP-regulated settings, and reinforcement learning.
Skills
Deep Learning For Biological Sequences And Structures: Secondary Structure And Developability Property Predictions For Vhhs, Antibodies And Miniproteins From Sequences And Structures, Transformer Models (Esm, Esmfold, Custom), Protein Generation From Natural-Language Specs, Antibody And Binder Optimization, In-Silico Design Loops.
Ml Infrastructure: Training And Evaluation Pipelines, Feature Stores, Scientific Data Systems, Biological Databases, Cloud And Local Training Workflows.
Nlp, Search & Retrieval: Sentence Embeddings, Semantic Search And Retrieval Over Hundreds Of Thousands Of Private Documents, Topic Clustering, Tf-Idf Baselines, Search-And-Indexing Pipelines, Metadata Generation And Data Representation For Retrieval, Embedding-Based Search At Production Scale.
Agentic & Conversational Ai: Task-Oriented Conversational Agents, Dialogue Management, Nlu, Reinforcement Learning For Dialogue Policy / Agent Decision-Making (Peer-Reviewed; 2 Patents), Embedded Voice Assistants.
Llm-Powered Systems: Shipped Internal Llm Copilots For Engineering And Scientific Workflows; Retrieval-Augmented Generation With Langchain / Llamaindex And Pgvector; Foundation-Model Apis, Prompting, And Evaluation.
Back-End Systems: Architecture, Design, And Implementation Of Production Rest Apis And Distributed, Cloud-Based Workflow Execution With Asynchronous Worker Infrastructure, In Python.
Machine Learning: Deep Learning, Transformer Models, Sentence Embeddings, Semantic Search, Nlp, Reinforcement Learning, Agentic / Dialogue-Policy Decision-Making, Llm Evaluation, Conversational Ai, Recommendation, Image Classification, Protein Generation, Antibody Optimization, Biological Sequence Modeling.
Bioinformatics Tools: Biopython, Biotite, Mmseqs2, Blast, Hmmer, Anarci, Alphafold, Esmfold 2, Boltz.
Frameworks & Nlp Libraries: Pytorch, Tensorflow, Keras, Scikit-Learn, Hugging Face Transformers, Sentence-Transformers, Spacy, Nltk, Esm / Esmfold.
Llm & Retrieval: Langchain / Llamaindex, Pgvector, Vector Databases, Retrieval-Augmented Generation, Search-And-Indexing Pipelines, Foundation-Model Apis And Prompting.
Ml Infrastructure: Training And Evaluation Pipelines, Feature Stores, Scientific Data Systems, Biological Databases, Embedding Pipelines, Cloud Ml Workflows.
Engineering & Back-End: Python, C/C++, C#, Java, Sql; Fastapi, Flask, Sqlalchemy, Pgqueue, Postgresql; Distributed Systems, Service Architecture, Linux.
Ai-Assisted Development: Heavy Day-To-Day User Of Claude Code And Cursor Across The Development Lifecycle.
Domains: Biotech And Drug Discovery, Pharmaceutical Manufacturing (Gxp), Regulated / High-Stakes Document Workflows, Automotive Infotainment, Enterprise Field Service.
Languages
Education
University of Karlsruhe
PhD · Computer Science · Karlsruhe, Germany
University of Karlsruhe
Diploma (MS equiv.) · Computational Linguistics and Computer Science · A
Statistics
Experience
Global experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Matthias is based in New York, United States and can operate in on-site, hybrid, and remote work models.
Matthias speaks the following languages: German (Native), English (Advanced), French (Advanced), Spanish (Intermediate), Japanese (Intermediate).
Matthias has at least 23 years of experience. During this time, Matthias has worked in at least 8 different roles and for 5 different companies. The average length of individual experience is 3 years and 10 months. Note that Matthias may not have shared all experience and actually has more experience.
Based on recent experience, Matthias would be well-suited for roles such as: Chief Technology Officer, Senior Vice President of Engineering, Director of Engineering.
Matthias's most recent position is Chief Technology Officer at Ordaos, Inc..
In recent years, Matthias has worked for Ordaos, Inc..
Matthias is most experienced in industries like Information Technology, Automotive, and Manufacturing. Matthias also has some experience in Aerospace and Defense, Energy, and Healthcare.
Matthias is most experienced in business areas like Information Technology, Product Development, and Research and Development. Matthias also has some experience in Strategy and Business Intelligence.
Matthias has recently worked in industries like Biotechnology.
Matthias has recently worked in business areas like Information Technology, Product Development, and Strategy.
Matthias holds a Doctorate in Computer Science from University of Karlsruhe and a Master in Computational Linguistics and Computer Science from University of Karlsruhe.
Matthias is immediately available part-time for suitable projects.
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