Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Knowledge Graph / AI Engineer with 10+ years of experience designing production data, machine learning, document intelligence, and semantic systems across legal technology, digital health, financial services, gaming, and cloud analytics. Experienced in ontology design, semantic modeling, taxonomies, RDF/OWL, SPARQL, knowledge graph construction, metadata management, and graph-enhanced retrieval. Hands-on translating domain requirements into scalable semantic models by integrating structured and unstructured data, validating graph consistency, and connecting knowledge layers with NLP, RAG, APIs, and cloud data platforms. Strong engineering background across Python, SQL, knowledge graph infrastructure, and cloud-native deployments with Kubernetes and major cloud providers.…Knowledge Graph / AI Engineer with 10+ years of experience designing production data, machine learning, document intelligence, and semantic systems across legal technology, digital health, financial services, gaming, and cloud analytics. Experienced in ontology design, semantic modeling, taxonomies, RDF/OWL, SPARQL, knowledge graph construction, metadata management, and graph-enhanced retrieval. Hands-on translating domain requirements into scalable semantic models by integrating structured and unstructured data, validating graph consistency, and connecting knowledge layers with NLP, RAG, APIs, and cloud data platforms. Strong engineering background across Python, SQL, knowledge graph infrastructure, and cloud-native deployments with Kubernetes and major cloud providers.

Eino Korhonen

AI Engineer, Data Scientist, Data Engineer, +2





Knowledge Graph / AI Engineer with 10+ years of experience designing production data, machine learning, document intelligence, and semantic systems across legal technology, digital health, financial services, gaming, and cloud analytics. Experienced in ontology design, semantic modeling, taxonomies, RDF/OWL, SPARQL, knowledge graph construction, metadata management, and graph-enhanced retrieval. Hands-on translating domain requirements into scalable semantic models by integrating structured and unstructured data, validating graph consistency, and connecting knowledge layers with NLP, RAG, APIs, and cloud data platforms. Strong engineering background across Python, SQL, knowledge graph infrastructure, and cloud-native deployments with Kubernetes and major cloud providers.…Knowledge Graph / AI Engineer with 10+ years of experience designing production data, machine learning, document intelligence, and semantic systems across legal technology, digital health, financial services, gaming, and cloud analytics. Experienced in ontology design, semantic modeling, taxonomies, RDF/OWL, SPARQL, knowledge graph construction, metadata management, and graph-enhanced retrieval. Hands-on translating domain requirements into scalable semantic models by integrating structured and unstructured data, validating graph consistency, and connecting knowledge layers with NLP, RAG, APIs, and cloud data platforms. Strong engineering background across Python, SQL, knowledge graph infrastructure, and cloud-native deployments with Kubernetes and major cloud providers.

Available to hire

Knowledge Graph / AI Engineer with 10+ years of experience designing production data, machine learning, document intelligence, and semantic systems across legal technology, digital health, financial services, gaming, and cloud analytics. Experienced in ontology design, semantic modeling, taxonomies, RDF/OWL, SPARQL, knowledge graph construction, metadata management, and graph-enhanced retrieval.

Hands-on translating domain requirements into scalable semantic models by integrating structured and unstructured data, validating graph consistency, and connecting knowledge layers with NLP, RAG, APIs, and cloud data platforms. Strong engineering background across Python, SQL, knowledge graph infrastructure, and cloud-native deployments with Kubernetes and major cloud providers.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Beginner

Language

English

Advanced

Czech

Fluent

German

Intermediate

Finnish

Advanced

Work Experience

Senior AI/ML Engineer at Wordsmith AI

February 1, 2024 - May 31, 2026

Led semantic modeling for Wordsmith’s enterprise legal AI platform, defining domain entities, relationships, taxonomies, and reusable schemas for contracts, clauses, parties, obligations, dates, risks, and legal playbook concepts across NDAs, DPAs, MSAs, and vendor agreements. Designed and evolved legal-domain ontologies using RDF/OWL concepts, controlled vocabularies, hierarchical taxonomies, and relationship constraints for downstream search, analytics, and AI workflows. Built knowledge-graph ingestion pipelines extracting entities and relationships from unstructured contracts, normalizing metadata, resolving identifiers, and mapping document content into a consistent semantic model using Python, NLP, schema validation, and automated quality checks. Developed graph-enhanced retrieval combining semantic relationships, metadata filtering, dense retrieval, BM25, RRF, and cross-encoder reranking, improving grounded-answer accuracy by 35% over 1M+ clauses. Implemented SPARQL-style grap

Senior AI Engineer at Ada Health

March 1, 2022 - January 31, 2024

Modeled clinical knowledge across 10,000+ symptoms/risk factors, 3,600 conditions, and 31,000 ICD-10 codes by defining concept hierarchies, relationships, mapping rules, and semantic constraints for symptom assessment and care-navigation workflows. Developed clinical NLP pipelines for entity recognition, symptom extraction, intent classification, and concept normalization using PyTorch/BERT/scikit-learn, achieving 95% F1 on targeted tasks and linking concepts to structured clinical vocabularies. Built semantic retrieval using Azure AI Search and Azure OpenAI with clinical metadata, concept relationships, curated knowledge sources, and citation-aware generation, improving response relevance and protocol adherence by 40%. Implemented FHIR-compatible integration services and canonical mappings connecting AI-generated assessments and clinical summaries to EHR systems and downstream workflows. Established MLOps and data-quality workflows with Azure Machine Learning, MLflow, CI/CD, and Ter

Senior ML Engineer | AI Consultant at Sopra Steria

April 1, 2018 - January 31, 2022

Led data and ML solutions for banking modernization and financial-crime programs, modeling customers, accounts, transactions, counterparties, devices, documents, and risk indicators as connected entities for fraud detection, transaction monitoring, KYC, and customer-risk analytics. Designed graph-oriented schemas and relationship models for financial entities combining transactional, behavioral, temporal, and network features. Developed production XGBoost fraud and risk-scoring models using graph-derived features, improving predictive performance by ~25%. Built scalable ingestion/transformation pipelines with S3, AWS Glue, EMR, Spark, and Airflow to normalize heterogeneous datasets with consistent identifiers and relationship/feature definitions. Created BERT-based NLP pipelines for KYC document processing and entity extraction (90%+ F1) mapping customer/organization/document/risk concepts into downstream analytical models. Implemented explainability and regulated environment monitor

Machine Learning Engineer at Amanita Design

August 1, 2016 - February 28, 2018

Designed structured player, session, event, progression, and purchase data models for large-scale behavioral analytics supporting retention, churn, lifetime-value, segmentation, and personalization use cases. Built retention/churn/LTV models using Python, Spark MLlib, XGBoost, and scikit-learn, improving retention-targeting effectiveness by 20%. Developed segmentation and personalization models from connected gameplay telemetry and progression signals, increasing engagement effectiveness by 18%. Processed billions of gameplay events with Apache Spark, Hadoop, Hive, and Kafka, standardizing event schemas and optimizing feature-engineering pipelines to reduce experiment iteration time by 35%. Implemented anomaly detection and A/B testing frameworks for bot detection, payment abuse, matchmaking analysis, and monetization optimization, reducing fraudulent activity by 30%.

Software Developer at GoodData

August 1, 2012 - June 30, 2014

Developed metadata and semantic-layer capabilities for GoodData’s multi-tenant cloud BI platform, supporting reusable business concepts, metrics, dimensions, relationships, and self-service analytics across enterprise workspaces. Designed logical data models, reusable metrics, metadata schemas, and relationship mappings translating business reporting requirements into consistent analytical structures across tenant workspaces. Built Java and JavaScript REST APIs for workspace administration, metadata management, and data integration workflows, improving API response latency by ~30%. Optimized PostgreSQL and MySQL schemas, indexes, and analytical queries, improving database performance by ~25% for metadata-intensive reporting workloads. Expanded automated testing and CI/CD (Jenkins) with Agile/Scrum practices to improve release reliability and metadata/analytics consistency.