Resume

Lijie Li · Data Scientist

Aalto UniversityKTH Royal Institute of Technology

Data scientist focused on multilingual retrieval, applied ML, and AI products. This site highlights selected systems work and case studies.

ContactView Case Studies

AI & Machine Learning

Deep LearningNLPSpeech RecognitionGenerative ModelsRAG SystemsData Mining

Engineering & Cloud

PythonPyTorchLangChainTritonSparkAzure AI FactoryGitLinuxAsync IO

Data & Analytics

SQLTableauMongoDBSPSSVisualizationStatistics

Focus

Research depth with product delivery

I build multilingual retrieval systems and production ML workflows, with an emphasis on measurable impact and clear evaluation.

Practice #1

Data Systems Practice

Day job energy goes into multilingual RAG stacks, speech models, and measurable retrieval governance. I prefer shipping explainable systems over publishing papers.

  • Agentic RAG orchestration
  • Knowledge graphs & KG ops
  • QLoRA + TPE fine-tuning
  • Triton + GPU tooling

Practice #2

Applied ML Delivery

Hands-on delivery of ML products: data pipelines, evaluation frameworks, and reliable deployments.

  • Retrieval evaluation & monitoring
  • Multilingual QA & reranking
  • Latency-aware inference stacks
  • Experiment design & reporting

Hybrid Case Studies

Where data products and visuals converge

Selected systems pairing measurable rigor with sensory storytelling.

AI SystemsVTT · Finland · 3rd place · 2025 AaltoAI Hackathon

Knowledge Graph Challenge on Heterogeneous Sources

Automated ingestion + semantic entity resolution with 100% traceability.

  • Hybrid search (Qdrant ANN + BM25) fused with RRF and Cross-Encoder rerankers.
  • HDBSCAN-powered entity resolution using `text-embedding-small` vectors.
  • Evaluation suite covering Hit Rate, MRR, and innovation lineage tracking.
AI ResearchAalto University · 2nd place

SNLP Challenge: Multilingual Speech + Toxicity

WER 0.0664 / CER 0.0123 with Wav2Vec2-BERT + SpecAugment.

  • Fine-tuned multilingual BERT with Triton acceleration and WandB tracking.
  • Benchmarked four multilingual toxicity models across English / German / Finnish.
  • Blended character-level noise defenses with balanced sampling strategies.
Data ProductsKunshan Yuanpai Trading · China

Recommendation & Uni-cloud Platform

Reduced query latency and improved personalization for merchandising teams.

  • DBSCAN clustering + MAB exploration to surface high-value customer cohorts.
  • Optimized MongoDB schema and SQL interfaces for order + inventory ops.
  • Built Tableau dashboards to translate raw telemetry into decisions.
AI EngineeringP&G · Finland · 3rd place · 2025 Junction

Agent Challenge on Automated Personalized Marketing

Multimodal n8n Agentic workflow for localized multi-channel assets.

  • Engineered a multimodal n8n Agentic workflow that adapts visual elements and optimizes text constraints for specific channels, achieving cultural localization.
  • Implemented a Self-Reflective and adaptive design with CoT reasoning to iteratively critique outputs and enforce safety guardrails.

Experience

Professional experience

View full CV on LinkedIn ↗

AI / Data Roles

Aug 2025 — Present

Data Scientist

Lexembed · Stockholm, Sweden

Designing multilingual knowledge engines that blend Agentic RAG, case-based reasoning, and knowledge graphs for legal intelligence teams.

  • Built a multi-hop QA flow that fuses entity extraction with graph traversals for rapid compliance research.
  • Introduced quantitative retrieval guardrails using RAGAS and automated regression suites for every release.

Aug 2023 — Mar 2024

Data Specialist (Intern)

International Digital Economy Academy · Shenzhen, China

Owned the end-to-end lifecycle for policy moderation models, from generative data augmentation to adversarial hardening and deployment.

  • Fine-tuned DeBERTaV3 with QLoRA + TPE, cutting VRAM usage by 80% and improving F1 by 5 points.
  • Used TextAttack adversarial suites to harden classifiers and validated robustness with macro-F1 and MCC dashboards.

Availability

Open to data science roles

Based in Stockholm. Open to onsite or remote ML roles across Europe and global teams.

EmailLinkedIn

Based in Stockholm · Shenzhen friendly · English / 中文